About the job
Join Our Innovative Team
About Ema
Ema is at the forefront of developing the world's largest agentic AI platform aimed at transforming enterprise productivity. Our cutting-edge technology empowers organizations to delegate repetitive tasks to Ema, the Universal AI employee, achieving remarkable efficiency improvements of up to 10 times. Founded by former leaders from Google, Coinbase, Flipkart, and Okta, we possess extensive expertise in product development and scaling. Our team consists of exceptional engineers hailing from prestigious companies such as Google, Microsoft Research, Facebook, Square, and Coinbase, as well as graduates from renowned institutions like Stanford, MIT, UC Berkeley, CMU, and the IITs.
Having raised over $60 million from leading investors, including Accel, Naspers/Prosus, Section32, SCB10X, Sozo Ventures, Hitachi Ventures, and notable angel investors like Sheryl Sandberg, Jerry Yang, and Dustin Moskovitz, Ema is headquartered in Silicon Valley with an additional hub in Bangalore, India. This hybrid role requires in-office attendance three days a week.
Position Overview
As the Engineering Lead within our Customer Value Engineering (CVE) team, you will play a crucial role in realizing our mission to reshape the future of work through the Universal AI Employee. You will lead the design of scalable, secure, and observable AI-driven workflows, translating customer aspirations into enterprise-grade solutions that yield measurable results. Your responsibilities will encompass everything from discovery workshops to production deployments.
Key Responsibilities:
- Workflow Discovery & Solution Design: Facilitate discovery workshops to gain insights into human workflows, pain points, data flows, and integration requirements. Transform business goals into comprehensive AI architecture blueprints that address integration, data management, security, and success metrics. Create and update “AI-Employee” design documents to guide the implementation process from blueprint to service level objectives (SLOs).
- Data Integration & Action Building: Utilize declarative connectors and APIs to ingest, normalize, and secure data from various enterprise systems (CRM, ERP, ATS, etc.). Develop and maintain reusable action blocks using REST/SOAP/RPA and seamlessly integrate them into agent-based workflows.
- Agentic Reasoning & Prompt Engineering: Construct and compose reasoning agents using state-of-the-art frameworks (e.g., LangChain, Semantic Kernel). Optimize prompts, establish memory management protocols, and define mesh topologies to facilitate robust agentic reasoning. Oversee prompt evaluation, experimental design (A/A, A/B), and rollback strategies.
- Human-AI Interaction: Define and implement user interaction paradigms to ensure seamless integration between human users and AI systems.
