Staff Enterprise AI Engineer

Peloton Interactive is looking to transform their enterprise tech strategy with AI adoption by hiring a Staff Enterprise AI Engineer. This role involves architecting and building the Operating System that enables teams to deploy AI Agents safely and at scale while guiding a team of engineers to execute the vision.

Responsibilities:

• Architect the "Intelligence & Integration" Layers
• Design and build a scalable Agentic Orchestration Platform (using LangChain, LangGraph, or custom frameworks) that allows internal developers to spin up autonomous agents
• Implement the "Integration Layer" ensuring all AI agents connect to internal APIs (Workday, Snowflake, SAP) via secure, standardized protocols (Model Context Protocol - MCP)
• Solve the "State Problem" for AI, architecting memory stores (Vector DBs like Pinecone/Weaviate) that persist context across user sessions
• Enforce "Security by Design"
• Partner with Security leadership to implement Identity Propagation. Ensure agents execute tasks using the user’s specific OAuth scopes, preventing privilege escalation
• Build "Data Clean Rooms" and PII masking pipelines to ensure sensitive member or employee data is never leaked to model providers
• Deploy EvalOps pipelines to automatically test models for hallucination and regression before they hit production
• Define the Engineering Standards
• Define the "Guide vs. Control" standards for the organization. Create the templates and libraries that allow analysts to "Vibe Code" (low-code/assisted coding) safely within our guardrails
• Perform rigorous code reviews for partner teams and vendors, ensuring high performance, low latency (<200ms), and cost efficiency
• Optimization of inference costs by implementing Semantic Caching and routing logic (e.g., routing simple queries to smaller/cheaper models)
• Leverage Kubernetes (EKS) to manage ephemeral compute resources for AI workloads
• You view AI as a distributed systems problem. You care about latency, rate limiting, and eventual consistency just as much as you care about prompt engineering
• You don't build "Science Projects." You build tools that solve specific business frictions (e.g., automating Content PR approvals or speeding up Supply Chain queries)
• You enjoy mentoring senior engineers and demystifying AI for non-technical stakeholders (from HR to Product)