About the job
At Confido, we are revolutionizing the AI infrastructure that drives consumer packaged goods (CPG) brands from deduction to production planning. Our integrated platform consolidates cash application, deductions, disputes, trade promotion management, forecasting, demand planning, and analytics, delivering significant time savings and intelligent decision-making capabilities for our customers.
We proudly serve over 200 brands, managing more than $20 billion in revenue, including notable names like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana. Recently, we have achieved exceptional growth and secured $15 million in Series A funding led by Footwork Ventures and Y Combinator to further accelerate our progress.
Your Role
As a Full-Stack Engineer (Early Career) at Confido, you will play a vital role in developing new product features and systems from the ground up. Collaborating closely with seasoned engineers, you will help create AI-driven workflows, enhance data systems, and design user-friendly product experiences tailored to our clients.
This position is perfect for an early-career individual eager to learn rapidly, take initiative, and contribute meaningfully to a growing product.
Primary Responsibilities
Develop and implement product features across the stack under team guidance.
Assist in building backend systems and data pipelines for financial data processing.
Support the development of AI-driven workflows incorporating computer vision and natural language processing.
Contribute to the design of user interfaces that simplify intricate financial workflows.
Collaborate with engineering teams, product managers, and occasionally clients to iterate on features.
Demonstrate a capacity for quick learning and progressively take on more responsibilities.
Examples of Challenges You Might Tackle
Developing systems for data extraction from financial documents.
Enhancing the scalability of data ingestion from diverse sources.
Contributing to analytics and forecasting tools for CPG brands.
Refining user experiences that convert complex data into actionable insights.
Qualifications
Required Skills
Hands-on experience through internships, academic projects, or equivalent in software engineering.
Solid programming fundamentals in any language.
A passion for technology and a desire to learn.

