Own ML/AI platform: lead training infra, serving, pipelines, registries, prod integrations
Set technical direction with Data Platform Architect
Build production ML systems: feature eng, training, deployment, monitoring
Drive GenAI/LLM eng: RAG, prompt engineering, cost-quality-safety tradeoffs
Develop agentic capabilities with MCP, stateless/stateful patterns
Own the serving layer: scalable ML services, API contracts, performance

🎯 Requirements

Senior engineering: 8+ yrs in software/ML, 5+ yrs prod ML
Technical leadership: mentor seniors, shape ML strategy
AWS ML expertise: SageMaker, Bedrock, AgentCore
Open-source ML tools: JupyterLab, Spark, MLflow
AWS platform know-how: S3, Athena, Redshift, Glue, Step Functions, Lambda
GenAI/LLM: RAG, prompt evaluation, QoS tradeoffs

🎁 Benefits

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

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