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Experience Level
Entry Level
Qualifications
The ideal candidate will possess strong programming skills, experience in software development, and familiarity with AI technologies. A Bachelor's Degree in Computer Science or a related field is preferred, along with a collaborative mindset and a willingness to learn.
About the job
fractional-ai is hiring a Software Engineer to join the team onsite in San Francisco. This role centers on building and improving technology that advances artificial intelligence.
Role overview
As a Software Engineer, you will work closely with others to develop and support projects that drive the company’s AI initiatives forward. The work involves collaborating with colleagues and contributing technical solutions in a team setting.
What you will do
Develop software for AI-driven projects
Collaborate with team members in the San Francisco office
Contribute ideas and technical expertise to ongoing initiatives
Requirements
Interest in technology and artificial intelligence
Ability to work onsite in San Francisco
Strong motivation to learn and contribute to team projects
About fractional-ai
fractional-ai is at the forefront of AI technology, delivering cutting-edge solutions that help businesses thrive. Our team is comprised of talented professionals dedicated to innovation, collaboration, and excellence.
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Search for Ai Data Engineer At Fluency San Francisco
Full-time|$150K/yr - $250K/yr|On-site|San Francisco
Join Fluency: Pioneering the Autonomous EnterpriseAt Fluency, we are on a mission to revolutionize enterprise intelligence. As an AI Data Engineer, you will be instrumental in constructing the data infrastructure that underpins our innovative solutions. Forget merely connecting dashboards; we are creating robust pipelines that extract, manage, and organize raw data from real-world workflows at an unprecedented scale.We seek an AI Data Engineer who will design and implement data systems crucial for our process conformance, productivity metrics, and AI impact assessment across leading Fortune 500 companies.The Challenge AheadYou will tackle the complexities of handling unrefined, real-world data signals such as screenshots, OCR text, application metadata, and user behavior events. Your goal will be to convert this unstructured data into actionable, reliable insights that our machine learning systems can utilize effectively, all while adhering to strict cost constraints.Core responsibilities include:Designing ingestion pipelines capable of processing millions of daily screenshots and behavioral events.Developing data validation and quality control systems to prevent model corruption due to data drift.Creating feature stores and serving infrastructure that balances data freshness with computational costs.Optimizing storage and querying for time-series behavioral data.Orchestrating intricate directed acyclic graphs (DAGs) that synchronize OCR, large language model (LLM) enhancements, and downstream aggregations.This is a groundbreaking role where you will define the playbook for data engineering in a rapidly evolving environment. Backed by top-tier venture capitalists like Accel, we are experiencing rapid growth and engagement with enterprises worldwide.You will collaborate closely with the founders and our engineering team, tackling technical challenges that encompass data engineering, LLM pipelines, and production systems.
Full-time|$150K/yr - $220K/yr|On-site|San Francisco
Join Fluency, the trailblazer in autonomous enterprise solutions.We invite you to be a part of a groundbreaking software initiative that is set to redefine enterprise operations. Dive into the future's data layer.Fluency is in search of a dynamic Full Stack Engineer to help build the autonomous enterprise.You'll tackle challenges that currently have no predetermined solutions. Our platform processes terabytes of workflow data for each enterprise client in real-time, enabling systems that map, relate, contextualize, and analyze work patterns throughout organizations. Consider it akin to the human genome project, but for enterprise workflows.In this role, you'll be tasked with inventing new data primitives and paradigms, which involves designing innovative data structures for work representation, developing pipelines capable of processing billions of events daily, and authoring whitepapers on methodologies that are yet to be established.You will be at the forefront of data science, where the conventional playbook has yet to be written.With backing from top-tier VCs such as Accel, we're reaching a pivotal moment with enterprises worldwide.You will collaborate closely with our founders and engineering team. The technical challenges are unprecedented: from real-time processing on a massive scale to creating a universal taxonomy for work applicable across every industry, and constructing systems designed to manage the most intricate enterprise data environments on the planet.
Fluency is revolutionizing how enterprises understand their internal processes. We provide clarity on how work gets done by capturing the intricacies that lie beneath tools and systems, transforming this data into actionable intelligence that executives can leverage.Our solutions empower clients to identify optimal areas for automation and AI implementation, validate the efficacy of transformation initiatives, and gain insights into operational realities that were previously obscured.We proudly collaborate with Fortune 10 companies and have recently secured a $6 million seed round led by Accel, with participation from DST Global Partners. As we expand our team in San Francisco, we invite you to join us on this exciting journey.The RoleAs a founding Mid-Market Account Executive, you will manage the full sales cycle targeting enterprises with 1,000 to 5,000 employees.You will engage with COOs, CIOs, and CEOs, often addressing challenges that they may not yet have the terminology to articulate. This role requires you to help define a new category of solutions.What Your Work Will EntailFocus on outbound pipeline generation while collaborating with a BDR on inbound leads. Hunting for new opportunities will be a key aspect of your role.Conduct in-depth discovery sessions with both executive and technical stakeholders to uncover hidden operational pain points instead of merely following qualification checklists.Embrace a pilot-first sales strategy, initiating with paid, narrowly defined pilots that address specific use cases, which you will collaboratively design with customers, ultimately converting them into enterprise agreements.Post-pilot, focus on expansion as our product gains traction across various business units and use cases, transforming early customers into your most significant accounts.Play a pivotal role in shaping the sales process alongside the founders, refining positioning, messaging, handling objections, and pricing as these elements are still in development.Be prepared for travel to conduct demos, workshops, and executive meetings as needed, with expectations for monthly or more frequent travel depending on deal activity.Current Deal MechanicsKey buyers include COO, CIO, CEO, Head of Transformation, and Head of Operations.The average contract value (ACV) starts at six figures, with potential for expansion.Sales cycles typically range from two to four months during the pilot phase, with some deals closing in under six weeks; full enterprise conversions may take longer.Pilots are paid engagements, concentrated on a single business unit or process.Expansion is driven by demonstrating value in one area, leading to broader organizational adoption.
Join Fluency in Revolutionizing the Autonomous EnterpriseAt Fluency, we challenge the limits of our models' capabilities. Unlike traditional chatbot prompt engineering, we are developing advanced evaluation frameworks and research systems that gauge, enhance, and validate enterprise intelligence at an unprecedented scale.We are seeking a Research Engineer who will be instrumental in designing experiments, constructing evaluation infrastructure, and enhancing model quality for our process conformance, productivity measurement, and AI impact analysis initiatives across Fortune 500 companies.Understanding the Problem SpaceYou will be at the forefront of developing methodologies and systems that assess the effectiveness of our models. With inputs ranging from screenshots, OCR text, application metadata to behavioral signals, the data can be complex and the truth often ambiguous. Your challenge will be to create robust evaluation frameworks that quantify model performance and pinpoint areas for improvement.Key responsibilities include:Crafting evaluation pipelines to measure accuracy, precision, and recall across various classification tasks.Creating ground truth datasets utilizing ambiguous real-world enterprise data.Conducting systematic prompt engineering experiments to enhance LLM performance.Developing A/B testing frameworks for model comparisons.Investigating innovative approaches to process understanding, activity classification, and intent extraction.Evaluating cost-accuracy trade-offs across diverse model architectures and prompting strategies.Establishing automated world-model training infrastructures based on our ontology.You will be pioneering methodologies that currently do not exist; you will define the playbook.Supported by top-tier VCs like Accel and prestigious research institutions such as Princeton, we are at a pivotal moment in our journey with enterprises worldwide.In this role, you will collaborate closely with founders and our engineering team to tackle technical challenges related to LLM evaluation, experimental design, and applied research.
Join a pioneering team of former Google engineers who have developed ground-breaking defensive technologies, such as Safe Browsing and reCAPTCHA. We are on a mission to confront an urgent challenge: combating the rising tide of adversarial AI attacks that threaten organizations globally.Operating in stealth mode, we are targeting a lucrative $5B+ market that is primed for innovation. Conventional detection methodologies are proving inadequate against the speed and sophistication of AI-driven assaults. Current adversaries are leveraging AI to engineer tailored, high-evasion attacks, leaving traditional systems vulnerable.Your Role:You will design a network of AI agents that are rapid, cost-effective, and precise, collaborating to identify and neutralize emerging threats. Your work will dive deep into real-time threat data, continuously evolving your agents in a fast-paced environment. These agents will function under an orchestration layer that fosters quick adaptation and learning.The Excitement of the ChallengeRapidly Evolving Models: The landscape changes daily; solutions that worked yesterday may be outdated today.Intelligent Adversaries: We are engaged in a real-time arms race against cunning, AI-enhanced attackers crafting sophisticated payloads.No Existing Playbook: We are forging new detection paradigms as swiftly as threats evolve. This high-stakes work places you in the heart of the action from day one.If you thrive on solving challenging problems with rapid feedback, this is your opportunity.Why We Are Positioned to SucceedExpansive Market: The market is vast at $5B and expanding quickly, while established players struggle to adapt.Proven Track Record: Our team has previously developed the foundational technology for Safe Browsing (serving over 5B users) and reCAPTCHA (protecting more than 5M websites) during our time at Google.Experienced Team: This is our third endeavor in creating a category-defining security enterprise, and we know how to scale our technology and our organization effectively.Deeply Integrated AI and Security: We embed AI from the outset rather than layering it on top.Top Talent: We hire only the highest achievers; many on our team were in the top 1% of engineers at Google. If you excelled in your previous role, you will fit right in.Agility: We prioritize speed and efficiency in everything we do.
About Liquid AIFounded as a spin-off from MIT CSAIL, Liquid AI specializes in creating versatile AI systems designed for optimal performance across various deployment platforms, including data center accelerators and on-device hardware. Our technology emphasizes low latency, minimal memory consumption, privacy, and dependability. We collaborate with leading enterprises in sectors such as consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we are on the lookout for exceptional talent to join our team.The OpportunityThe Data team at Liquid AI drives the development of our Liquid Foundation Models, focusing on pre-training, vision, audio, and emerging modalities. With the stagnation of public data sources, the effectiveness of our models increasingly relies on specially curated datasets. We are seeking engineers with a machine learning mindset who can efficiently gather, filter, and synthesize high-quality data at scale.At Liquid AI, we regard data as a research challenge rather than an infrastructural issue. Our engineers conduct experiments, design ablations, and assess how data-related decisions impact model quality. We will align you with a team where you can experience rapid growth and make a significant impact, be it in pre-training, post-training reinforcement learning, vision-language, audio, or multimodal applications.While we prefer candidates in San Francisco and Boston, we are open to considering other locations.What We're Looking ForWe are in search of a candidate who:Thinks like a researcher and executes like an engineer: You should be able to formulate hypotheses, conduct experiments, and evaluate results. Our engineers produce research-level code while our researchers implement production systems.Learns quickly and adapts: You will be working in rapidly evolving modalities, so the ability to quickly grasp new domains and thrive in ambiguity is essential.Prioritizes data quality: We hold data quality in high regard; tasks such as filtering, deduplication, augmentation, and evaluation are key responsibilities, not afterthoughts.Solves problems autonomously: Data engineers operate within training groups (pre-training and multimodal). While collaboration is crucial, we expect ownership and self-direction.The WorkDevelop and maintain data processing, filtering, and selection pipelines at scale.Establish pipelines for pretraining, midtraining, supervised fine-tuning, and preference optimization datasets.Design synthetic data generation systems utilizing large language models (LLMs), structured prompting, and domain-specific generative techniques.
About David AIDavid AI is pioneering the audio data research landscape, applying a rigorous R&D approach to dataset development akin to the methodologies used in AI labs for model creation. Our goal is to integrate AI seamlessly into real-world applications, with audio serving as the perfect entry point due to its inherent versatility and human connection. As the audio AI field progresses, the demand for high-quality training data becomes critical, and that's where David AI excels.Founded in 2024 by a team of experienced engineers and operators from Scale AI, David AI has quickly gained traction, serving prominent clients among FAANG companies and AI research labs. Recently, we secured a $50M Series B funding round from esteemed investors including Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, and First Round Capital.Our team embodies intelligence, humility, ambition, and a close-knit ethos. We are on the lookout for exceptional talent in research, engineering, product, and operations to join us in advancing the frontiers of audio AI.About Our Engineering TeamAt David AI, our engineering team is responsible for constructing the pipelines, platforms, and models that convert raw audio into valuable data for top AI labs and enterprises. We pride ourselves on our collaborative environment, comprising product engineers, infrastructure specialists, and machine learning experts dedicated to leading the charge in audio data research.We operate at a fast pace, taking ownership of our projects from conception through to production. Our team develops real-time processing pipelines capable of managing terabytes of audio data daily while deploying innovative generative audio models.About This RoleAs a Product Engineer at David AI, you will design and implement state-of-the-art tools that enable our users to leverage audio data effectively for training their AI models. You will collaborate closely with researchers to continuously refine our data collection methodologies.Your ResponsibilitiesDeliver full-stack features that will be utilized by thousands of users on a daily basis.Develop scalable systems that create essential data processing pipelines, extracting actionable insights from terabytes of audio data each day.Construct, deploy, and assess LLM and DSP-based solutions to enhance our clients' comprehension of intricate features within our datasets.Rapidly iterate on research hypotheses by collaborating with researchers and the operations team to deploy enhancements efficiently.
About David AIDavid AI is a pioneering audio data research company that applies a rigorous R&D framework to data development, akin to that of leading AI labs. Our mission is to seamlessly integrate AI into everyday life, recognizing that audio serves as a natural interface. As the demand for advanced audio AI grows, the need for high-quality training data becomes critical—this is where David AI excels.Founded in 2024 by a talented team of former Scale AI engineers and operators, we have rapidly secured partnerships with major FAANG companies and AI laboratories. Recently, we raised $50M in Series B funding from prestigious investors like Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital, and others.Our team is composed of sharp, humble, and ambitious individuals who collaborate closely. We are eager to welcome the brightest minds in research, engineering, product, and operations to join us in advancing the frontiers of audio AI.About our Data Operations TeamThe Data Operations team is the powerhouse behind David AI's Data Factory, converting raw audio into exceptional training datasets for top AI labs. Our goal is to develop and manage new data pipelines on a grand scale.This entails starting with a model capability we aim to unlock, experimenting with various data shapes and collection strategies, and validating these approaches with researchers. Once we identify a successful method, we industrialize it by creating reliable, efficient, and high-quality audio processing pipelines. Our team thrives in ambiguous environments, adept at both prototyping innovative workflows and managing extensive production systems.About This RoleAs the Data Product Operations Lead, you will be instrumental in propelling the Data Factory at David AI. Your responsibilities will include designing and scaling pipelines that transform raw audio into valuable datasets for leading AI labs. You will take full ownership of data products from initial prototypes to large-scale implementations, actively building workflows, validating them with researchers, and ensuring their reliability at production levels.In This Role, You WillOversee the complete success of a data pipeline, from initial experiments to scaling up production systems that produce high-quality audio data in significant volumes.Design and operate pipelines that maintain reliability, quality, and efficiency while processing an extensive volume of audio data.
Join Our Innovative Team at Simple AIAt Simple AI, we are transforming enterprise communications through cutting-edge voice AI agents. Our highly realistic agents empower leading companies such as DoorDash, xAI, and Omaha Steaks to efficiently manage a variety of phone operations, including customer support, order processing, and lead qualification.As we experience exponential growth and a surge in customer demand, we are seeking a few founding software engineers to help us navigate this exciting journey and develop systems for the future. Our passionate team operates from our vibrant San Francisco office five days a week, driven by a shared vision of leveraging AI to make a significant impact in the world.We are proud to be backed by esteemed investors and operators, including Y Combinator, Massive Tech Ventures, and industry leaders such as Michael Seibel (Twitch), Jared Friedman (Scribd), and more.
About AbridgeFounded in 2018, Abridge is dedicated to enhancing understanding in healthcare. Our innovative AI-driven platform is designed specifically for medical conversations, streamlining clinical documentation and allowing healthcare professionals to concentrate on what truly matters—their patients.Our enterprise-grade technology converts patient-clinician discussions into structured clinical notes in real-time, with robust EMR integrations. Leveraging our unique Linked Evidence and auditable AI, we provide the only solution that aligns AI-generated summaries with factual data, enabling providers to trust and verify outputs efficiently. As trailblazers in generative AI for healthcare, we are establishing industry benchmarks for the ethical integration of AI across health systems.We are a dynamic team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers committed to empowering individuals and making healthcare more intelligible. Our offices are located in San Francisco's Mission District, New York's SoHo neighborhood, and Pittsburgh's East Liberty.The RoleJoin our rapidly expanding US-based Data Engineering team as a Data Engineer and play a pivotal role in revolutionizing the medical field with our generative AI products. In this essential position, you will design and optimize large-scale data infrastructure to inform business strategies and drive machine learning research.What You’ll DoDevelop and sustain scalable data services, pipelines, and storage solutions for the ingestion of unstructured application data for machine learning training and evaluation.Create and oversee OLAP databases, ELTs, and general data tools to support analytics, business decision-making, and product features.Collaborate closely with frontend and backend engineers, product managers, and analysts.Enhance data infrastructure to improve system throughput, latency, and reliability.Identify and resolve issues detected through data operation monitors, tools, and reports.Design data integration solutions and establish a data quality framework.What You’ll Bring5+ years of experience in Data Engineering or Backend Engineering focused on data systems.Proficiency in at least one general-purpose programming language (e.g., Python, Java, Scala) and SQL (any variant).Experience with at least one modern cloud service provider (GCP, AWS, Azure, etc.).
Join the Mercor TeamAt Mercor, we are pioneers at the crossroads of labor markets and artificial intelligence research. Collaborating with top AI labs and enterprises, we provide the crucial human intelligence that drives AI development.Our extensive talent network empowers more than 30,000 experts who collectively generate over $2 million a day, training cutting-edge AI models by sharing invaluable knowledge and context that goes beyond mere code. We are dedicated to establishing a new work paradigm where expertise fuels AI progress, and we are looking for driven individuals to join our ambitious and fast-paced team.As a profitable Series C company valued at $10 billion, Mercor emphasizes teamwork in our new San Francisco headquarters, where we work in-person five days a week.Your Role as a Data EngineerWe are seeking a passionate Data Engineer who can bring a full-stack perspective to our data functions. In this role, you will create and maintain robust data pipelines that support our Data Science, Engineering, and Product teams, ensuring seamless data flow across the Mercor organization.Your primary focus will be on data reliability, availability, and timeliness, working closely with our Data Science team and various partner functions to enhance our data capabilities.Key ResponsibilitiesDeveloping robust data pipelines to ingest, transform, and consolidate data from various sources, such as MongoDB, Airtable, and production databases.Designing dbt models and transformations to standardize and unify disparate data tables into clean, production-ready schemas.Implementing scalable and fault-tolerant data workflows using tools like Fivetran, dbt, SQL, and Python.Collaborating with engineers, data scientists, and business stakeholders to ensure data accuracy, availability, and usability.Owning data quality and reliability from ingestion to consumption across the data stack.Continuously monitoring and enhancing pipeline performance and scalability.QualificationsProven experience in data engineering, with strong proficiency in SQL, Python, and modern data stack tools such as Fivetran, dbt, Snowflake, or similar.Experience in building and maintaining large-scale data pipelines and workflows.Strong problem-solving skills and a collaborative mindset, with a focus on effective communication.
About the RoleJoin our innovative team at saris-ai, a pioneering applied AI startup based in San Francisco and Montreal. We are on a mission to redefine the banking industry by addressing a $100 billion annual challenge that is rapidly evolving. Our cutting-edge multi-turn AI agentic systems are at the forefront of this transformation.Our objective is to develop automated solutions that require sophisticated long-context reasoning, seamless tool integration across legacy systems, and stringent compliance mechanisms, particularly in scenarios where conventional answers are elusive.With successful real-world deployments and a rapidly expanding client base, we are seeking passionate and technically adept builders eager to make a significant impact from the start.We are in search of an AI Sales Engineer who will play a pivotal role in enhancing productivity and efficiency within financial institutions through innovative AI solutions. In this role, you will lead discovery calls with various departments to identify workflow challenges and design impactful AI-driven solutions. You will serve as the technical authority during sales cycles, assisting clients in recognizing problems, framing solutions, and articulating ROI.This position combines elements of customer engagement and workflow analysis.Your Key Responsibilities Include:Conduct discovery and technical scoping calls with potential clients to uncover operational inefficiencies in financial institutions.Develop workflow maps and reports to identify bottlenecks and pinpoint opportunities for agentic AI automation.Collaborate with the Sales team to co-manage the pre-sales process from initial discovery to proposal delivery.Engage with executive stakeholders, presenting clear and compelling insights on how Agentic AI can deliver measurable ROI and transform operations at scale.Work closely with cross-functional teams including sales, customer success, and product to ensure customer satisfaction and success.
fractional-ai is hiring a Software Engineer to join the team onsite in San Francisco. This role centers on building and improving technology that advances artificial intelligence. Role overview As a Software Engineer, you will work closely with others to develop and support projects that drive the company’s AI initiatives forward. The work involves collaborating with colleagues and contributing technical solutions in a team setting. What you will do Develop software for AI-driven projects Collaborate with team members in the San Francisco office Contribute ideas and technical expertise to ongoing initiatives Requirements Interest in technology and artificial intelligence Ability to work onsite in San Francisco Strong motivation to learn and contribute to team projects
Join Saris AI as an AI Systems Engineer, where you will play a pivotal role in designing and implementing innovative solutions that leverage artificial intelligence technologies. You will collaborate closely with cross-functional teams to develop AI systems that enhance our products and services, driving impactful results for our clients.
Join David AI as a Staff Product EngineerAt David AI, we are pioneering the field of audio data research, applying a rigorous R&D methodology to create robust datasets that empower AI models. Our vision is to integrate AI seamlessly into daily life, with audio serving as the key medium. As the demand for high-quality training data grows, we position ourselves as the solution.Founded in 2024 by a team of seasoned engineers from Scale AI, we quickly garnered the trust of leading FAANG companies and AI labs. Our recent $50M Series B funding round was led by prestigious investors including Meritech and NVIDIA, underscoring our potential in the audio AI landscape.We pride ourselves on our dynamic, collaborative, and ambitious team, and we are on the lookout for exceptional talent in research, engineering, product, and operations to help us redefine audio AI.About Our Engineering TeamOur engineering team is at the forefront of innovation, building the infrastructure, platforms, and models that convert raw audio into valuable data for top-tier AI labs and enterprises. We are a close-knit group of product engineers, infrastructure experts, and machine learning specialists who are dedicated to establishing the first-ever audio data research organization.We operate with agility, taking ownership of our projects from inception to deployment, delivering production-ready solutions on a daily basis. Our engineers design real-time pipelines that manage vast amounts of speech data while deploying advanced generative audio models.Your RoleAs a Staff Product Engineer, you will spearhead our Product Engineering team, developing state-of-the-art products that enable our clients to harness audio data effectively for model training. You will collaborate with researchers to continually refine our data collection methodologies.Your ResponsibilitiesLead the development of full-stack features, rapidly iterating to deliver daily innovations to our users.Construct scalable systems that process terabytes of audio data and extract actionable insights.Deploy and assess LLM- and DSP-based solutions to enhance customer understanding of their data.Facilitate research iterations and deployment interfaces for data collection in collaboration with researchers and operations.
Role OverviewLocation: San Francisco, CA Work Model: In-officeAbout Effective AIAt Effective AI, we are pioneering the future of work, focusing on sophisticated AI solutions for complex knowledge tasks rather than simple, repetitive functions. Our goal is to develop advanced AI Teammates that excel in intricate workflows and collaborate seamlessly with human professionals. Our initial challenge is to revolutionize the trillion-dollar U.S. Property & Casualty insurance sector, an area rich in data and complexity, ideal for our innovative approach.We have successfully secured $10 million in seed funding from prominent investors including Lightspeed Ventures and Valor Equity Partners.Our passionate team operates out of San Francisco, where we value in-person collaboration to address these pressing challenges.Your ResponsibilitiesAs a Founding Software Engineer, you will be an integral member of our founding team, significantly influencing the design and development of our core product from inception. You will confront critical challenges in agentic AI, crafting Teammates capable of managing essential insurance functions such as underwriting and claims processing.Specifically, you will:Facilitate long-term task completion by creating the foundational architecture for AI agents to plan and execute multi-step processes reliably over prolonged interactions.Develop advanced reasoning functionalities, enabling agents to make informed decisions based on ambiguous or incomplete information, akin to human experts.Create intelligent, tool-utilizing agents capable of selecting and employing a variety of external tools—APIs, databases, web searches, and Excel-based pricing algorithms—to gather information and take decisive actions.Design adaptive and learning systems, equipping our AI Teammates to learn from feedback and adjust to evolving conditions such as regulatory changes or market dynamics.Your ProfileWe seek an innovative and driven builder excited to tackle substantial challenges.You possess a solid foundation in computer science and remarkable problem-solving capabilities, evidenced by impactful projects or previous experience.Your genuine enthusiasm for AI fuels your passion for tackling complex issues.
About RoxRox is pioneering an AI-native revenue operating system designed specifically for modern go-to-market teams. Supported by notable investors such as Sequoia, GV, and General Catalyst, we are collaborating with ambitious enterprise teams to transform fragmented CRM workflows into intelligent, autonomous systems. Rox seamlessly integrates data across the GTM stack, deploys AI agents for tangible tasks, and equips revenue leaders with a clear, unified view of the key drivers of success.As a nimble Series A startup, we are challenging one of the most established categories in software—achieving victory through a blend of deep technical expertise and an unwavering focus on utility.About the Solutions Engineering TeamAt Rox, the Solutions Engineering team is not merely a support function; it plays a crucial role in shaping products and defining deals. This team operates at the intersection of Sales, Product, and Engineering, tasked with translating Rox’s technical capabilities into compelling customer value.You will join the foundational team in San Francisco, reporting directly to our Solutions Engineering leader. Working alongside three current Solutions Engineers, you will help establish how this function scales in SF. The practices you develop—such as how we demo, scope, integrate, and sell—will serve as the blueprint for the future of the company.About the RoleThis is a founding-level Solutions Engineer role for individuals who are technical, customer-focused, and passionate about redefining the sales engineering landscape.Your responsibilities will involve engaging directly with live deals: conducting technical discovery, crafting integrations, and leading demonstrations that clearly illustrate how Rox fits within customers’ data and GTM environments. This role transcends mere execution; you will identify inefficiencies in the sales process and implement improvements—enhancing demo experiences, refining technical narratives, and setting higher standards for those who follow.If you thrive on being the go-to person who can delve deeply into technical aspects while simplifying complexity for others, this role is tailored for you.What You’ll DoQuickly become a product expert, gaining deep insights into Rox’s architecture, use cases, and customer workflows.Collaborate closely with Sales to deliver impactful technical demos and support deals from initial contact to closure.Design and articulate integrations across data warehouses, CRMs, AI agents, and contemporary GTM tools.Facilitate technical discovery discussions that uncover genuine customer challenges rather than just stated requirements.Translate complex technical information into easily digestible insights for stakeholders.
Saris AI develops advanced AI automation for the banking sector, with teams in San Francisco, Montreal, and Toronto. The company addresses large-scale automation challenges, focusing on long-context reasoning, integrating with legacy systems, and meeting strict compliance needs. Saris AI’s AI agents are already active in production, supporting real customer workflows as the business expands. Role overview The San Francisco engineering team is seeking an Engineering Manager. This leader will guide engineers through shifting priorities and frequent ambiguity. The position involves building and leading teams, managing projects from concept to launch, and ensuring the delivery of reliable software that powers AI-driven products. What you will do Build and lead engineering teams focused on automation and AI Oversee software projects from initial idea through production launch Adapt to changing requirements and priorities as the company grows Address the technical challenges unique to deploying software in AI systems Requirements Proven experience building and leading engineering teams History of delivering software projects from start to finish Comfort working in environments where priorities and requirements shift quickly Understanding of the complexities involved in AI-driven software deployment Location This role is based in San Francisco.
Join Hilbert, a pioneering data science-driven growth engine that empowers B2C teams with insightful predictive analytics on user behavior, revenue drivers, and sustainable growth strategies. Our platform is designed to transform lengthy decision-making processes into swift, actionable insights.From Fortune 10 enterprises to cherished brands like FreshDirect, Blank Street, and Levain Bakery, industry leaders rely on Hilbert for their growth initiatives. We are also collaborating with top-tier AI companies to further enhance our offerings.We are in search of an AI Engineer who possesses the ability to develop robust AI systems from conception to deployment, embodying the agility and ownership characteristic of a startup culture.This role goes beyond mere model fine-tuning; you will take charge of critical components of the AI infrastructure that drive Hilbert's demand intelligence platform, rapidly deliver solutions in a dynamic environment, and articulate your work and its significance to the broader team. If you excel in writing clean Python code, think systemically, and are eager to create AI products that yield tangible business results, we would love to connect with you.THE ROLEYou will collaborate closely with the founding team, as well as product, data, and go-to-market teams, to design, develop, and enhance the AI systems central to Hilbert's operations. Expect a high-autonomy, high-ambiguity environment where the requirements are fluid, approaches adapt, and those closest to the challenges lead the way.What you'll do:Design, build, and maintain AI-driven features and pipelines that cater to enterprise clients at scale.Architect and implement agent-based workflows utilizing LangChain, LangGraph, or similar orchestration frameworks.Oversee systems from experimentation through production deployment and ongoing monitoring.Develop and optimize evaluation pipelines to assess, validate, and enhance AI system performance.Engage closely with the founding team and cross-functional collaborators, clearly communicating trade-offs, progress, and technical decisions.Make pragmatic engineering choices amidst uncertainty — ship, learn, and iterate.Influence the technical trajectory of the AI stack as the company expands.WHO THRIVES IN THIS ROLEWe value your thought process and execution over the number of years on your resume.The profile:You are a proficient Python engineer. Your code is clean, testable, and ready for production.
About the RoleWe are on the lookout for a skilled Forward Deployed AI Engineer to join our dynamic team at Stack AI. This position is crucial for implementing enterprise-level AI solutions with an emphasis on Retrieval-Augmented Generation (RAG) pipelines and large language model (LLM) workflows. Your contributions will significantly enhance our offerings to Fortune 500 companies and enterprises across diverse sectors.Role Overview:In this role, you will seamlessly integrate large language models into enterprise systems, collaborating with strategic accounts to tailor solutions that meet their technical needs. Utilizing the Stack AI platform, you’ll engage with clients to co-create innovative solutions that address their evolving challenges.Key Responsibilities:Enhance and maintain solutions for strategic accounts using the Stack AI platform.Analyze and document requirements and relationships within target enterprise offices.Identify opportunities and provide insights to shape our go-to-market strategy.Directly contribute to the Stack AI codebase, transforming customer feedback into enhancements for the Python backend and React/Next.js TypeScript frontend.Project future opportunities and secure high-value contracts.Draft proposals, present to stakeholders, and lead engaging product demonstrations.Promote Stack AI at enterprise conferences and events.
Jun 27, 2025
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