Sr. AI Engineer (Full Stack)

ABOUT THE ROLE

We at Peloton are looking for a scrappy, creative and fast-moving AI Engineer. 

You’ll take raw ideas and rapidly transform them into production-grade applications that empower our global organization. You will architect the Intelligence & Integration Layers that connect autonomous agents directly into Peloton’s enterprise infrastructure.

We don't care about your specific stack or what programming language you grew up with. We care about systems thinking, engineering fundamentals, product sense, and your ability to ship fast. Work at the bleeding edge of the AI ecosystem with top-tier tools and compute resources. What you build goes directly into the hands of real users in days, not months.

YOUR DAILY IMPACT AT PELOTON

• Take ambiguous problems and turn them into functional, high-performing AI features and standalone tools


• Solve the "State Problem" for AI by building memory architectures and vector stores (Pinecone, Pgvector) that maintain context while strictly adhering to data retention and deletion policies


• Build pipelines and entity-resolution logic that connect data across CRM, ERP, CPQ, and marketing systems (e.g. Salesforce, SAP, BigQuery) into a single, reliable source of truth agents can act on


• Embed with Peloton business units to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value


• Embed closely with stakeholder teams, understand their needs, and guide adoption of what you build


• Share field feedback that helps other teams understand where the models succeed and where they can improve


• Deploy continuous evaluation pipelines to test models for hallucinations, prompt injections, data leakage, and performance regressions before code hits production


• Implement Semantic Caching and smart routing logic (directing routine queries to smaller, cheaper models) to maintain low latency and efficient inference costs

YOU BRING TO PELOTON

• 5–7+ Years of General Software Engineering. Strong foundational software engineering skills (distributed systems, async patterns, API design, microservices, and databases)


• Comfortable pivoting to whatever language or framework gets the job done fastest


• Hands-on experience deploying RAG (Retrieval-Augmented Generation) and Agentic Workflows into production using LLM APIs, vector databases, and orchestration frameworks


• Proven track record building and maintaining pipelines across fragmented enterprise systems (CRM, ERP, CPQ, marketing platforms) with attention to entity resolution, schema design, and data quality — not just consuming clean data once it exists


• Cutting-Edge Stack: Work at the bleeding edge of the AI ecosystem with top-tier tools and compute resources.


• Direct Impact: What you build goes directly into the hands of real users in days, not months.

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