AI Enterprise Architect
About The Position
ABOUT THE ROLE Reporting directly into the CIO organization, you will be the lead architect and "ace technologist" responsible for the next era of Peloton’s internal evolution: Agentic AI. You will go beyond simple chatbots to build autonomous and semi-autonomous AI agents that execute complex workflows across Finance, Supply Chain, Marketing, Legal, and the People Team. This role is for a hands-on coder who can also set the strategic technical roadmap for enterprise-wide automation. YOUR DAILY IMPACT AT PELOTON Architect and code multi-agent systems that can reason, use tools, and execute end-to-end business processes (e.g., automated financial reconciliation, legal contract analysis, or supply chain demand forecasting) Partner with leaders in Finance, Marketing, Legal, and HR to translate their complex operational challenges into concrete AI architectures Evaluate the latest agentic frameworks and LLM providers to decide when to leverage third-party tools and when to build proprietary enterprise solutions Design highly available inference services and manage model serving at scale, ensuring these agents integrate seamlessly with existing corporate service meshes Implement "Security by Design," creating automated guardrails for PII/PHI filtering and mitigating prompt injection to ensure enterprise data remains secure Optimize the "Total Cost of Ownership" by managing trade-offs between agent reasoning depth (latency) and compute costs through intelligent caching and specialized routing YOU BRING TO PELOTON 8–10+ years in software engineering, with at least 2 years of deep focus on AI/ML infrastructure or data engineering at scale
Requirements
- 8–10+ years in software engineering, with at least 2 years of deep focus on AI/ML infrastructure or data engineering at scale
- Mastery of Python, Go, or Java/Scala, with a strong grasp of distributed systems and microservices
- Proven experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and deep understanding of vector databases (e.g., Pinecone, Milvus, Weaviate)
- Hands-on experience with modern data stacks (Spark, Kafka, Snowflake, Databricks) and cloud environments (AWS, GCP, or Azure)
- Expert knowledge of Kubernetes, Docker, and CI/CD patterns specifically for machine learning lifecycles
Responsibilities
- Architect and code multi-agent systems that can reason, use tools, and execute end-to-end business processes (e.g., automated financial reconciliation, legal contract analysis, or supply chain demand forecasting)
- Partner with leaders in Finance, Marketing, Legal, and HR to translate their complex operational challenges into concrete AI architectures
- Evaluate the latest agentic frameworks and LLM providers to decide when to leverage third-party tools and when to build proprietary enterprise solutions
- Design highly available inference services and manage model serving at scale, ensuring these agents integrate seamlessly with existing corporate service meshes
- Implement "Security by Design," creating automated guardrails for PII/PHI filtering and mitigating prompt injection to ensure enterprise data remains secure
- Optimize the "Total Cost of Ownership" by managing trade-offs between agent reasoning depth (latency) and compute costs through intelligent caching and specialized routing
Benefits
- Medical, dental and vision insurance
- Generous paid time off policy
- Short-term and long-term disability
- Access to mental health services
- 401k, tuition reimbursement and student loan paydown plans
- Employee Stock Purchase Plan
- Fertility and adoption support and up to 18 weeks of paid parental leave
- Child care and family care discounts
- Free access to Peloton Digital App and apparel and product discounts
- Commuter benefits and Citi Bike Discount
- Pet insurance and so much more!
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
