Own ML/AI platform: training infra, serving, pipelines, registries, prod integrations
Set technical direction with architecture standards and tooling
Build production ML systems with AWS and open-source tooling
Drive GenAI, LLM engineering, RAG, prompt engineering, and agentic workflows
Develop agentic capabilities with MCP and guardrails for regulated env
Own the serving layer and design scalable ML services

🎯 Requirements

Senior engineering: 8+ yrs in software/ML, 5+ in production ML
Technical leadership in ML strategy and mentoring
AWS ML expertise: SageMaker, Bedrock, AgentCore
Open-source ML tooling: JupyterLab, Spark, MLflow
AWS platform: S3, Athena, Redshift, Glue, Step Functions, Lambda
GenAI/LLM: RAG, prompting, eval, tradeoffs

🎁 Benefits

Equity
Flexible Time Off
Medical/dental/vision coverage
Disability and life insurance
Learning and career development
Remote-work setup reimbursement

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