Software Engineer, AI Foundation (Mid-Senior level)

Requirements

• We are hiring software engineers across all levels. Most of our open roles are targeting individuals with at least 3 years experience if past work is highly relevant
• BS or higher, in Computer Science or related technical field involving coding (e.g. physics or math)
• 3+ years of backend or full-stack software engineering experience in a production environment.
• Strong Python proficiency; experience with async frameworks and distributed systems is a plus.
• Hands-on experience building or operating LLM-based applications - RAG pipelines, tool use, agents, or eval systems.
• Experience with data pipelines, job scheduling (Airflow or equivalent), and vector databases or embedding-based search.
• Comfort with observability tooling: tracing, logging, metrics, and alerting in production AI systems.
• A track record of owning problems end-to-end - you care whether things work in production, not just whether they shipped.
• Ability to drive ambiguous, open-ended problems to a conclusion without a lot of hand-holding.
• A platform mindset: you think about who else will use what you build and design for reuse, not just the immediate use case.
• Exposure to AI-driven automation or interest in working with AI/ML teams to build intelligent workflows.
• Familiarity with LangChain, LangGraph, or similar agent orchestration frameworks.
• Experience with document parsing or OCR pipelines (PDF, DOCX, XLSX extraction).
• Background in ML platform, developer tooling, or internal platform engineering.
• Prior work on evaluation frameworks for AI/ML systems.
• Experience at a fast-moving startup with broad, cross-functional responsibilities.
• Exposure to procurement, finance, or enterprise SaaS domains.
• The salary range for this role is $160,000 - $260,000. The salary for this position is determined based on a variety of job-related factors that may include location, relevant experience, education, or particular skills and expertise.

Benefits

Additional Information

About Zip Zip is the AI platform for enterprise procurement - built for humans and agents working together. By orchestrating procurement across teams, tools, and suppliers with the help of AI agents, companies can secure the resources they need to innovate faster than ever before. The world's most influential enterprises trust Zip, including T-Mobile, OpenAI, AMD, Mars, Dollar Tree, and more. Together they've saved over $8 billion and processed over $500 billion in spend. Zip's team includes product leaders from Apple, Airbnb, and Meta, as well as former procurement leaders from United Health, Sanofi, MGM Resorts, Discover, and NASA. Backed by Adams Street, Alkeon, BOND, CRV, DST, Tiger Global, and Y Combinator, Zip has raised $371 million, most recently at a $2.2 billion valuation and has been recognized by Forbes Fintech 50, Fast Company's Most Innovative Companies, Inc. Best in Business, and LinkedIn Top Startups. Your Role As a Software Engineer on the AI Foundations team, you will own the platform that powers every AI-driven product at Zip. This is not a feature team - you are building the shared infrastructure that multiplies the effectiveness of every engineer and product at the company. Your work spans agentic orchestration, document processing pipelines, retrieval and memory systems, and the eval infrastructure that makes it all reliable. You will operate with significant technical autonomy, regularly defining the right approach from scratch in a field where established answers are still being written. If you find that energizing rather than uncomfortable, this role is built for you. You Will Design and build the core agentic platform powering Zip's AI products, including orchestration, memory, retrieval, and document processing infrastructure. Own end-to-end delivery of platform capabilities - from architecture decisions through production - with real influence over how the broader engineering organization builds AI. Partner closely with every product team at Zip to understand their needs, surface shared patterns, and ship reusable infrastructure that raises quality across Intake AI, Chatbot, IP Agent, Contract Orchestration, and Payments simultaneously. Push the frontier of applied AI engineering: LLM orchestration with LangGraph, RAG pipelines, agentic document parsing, and self-correcting memory systems. Build and evolve eval frameworks and observability tooling that make AI systems measurably more reliable over time. Translate ambiguous, open-ended problems into well-scoped technical solutions, without waiting for a playbook that may not yet exist.

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