Description

•       Python  •  SQL  •  AWS Bedrock & Claude

•       Hands-on ML engineering in Python (PyTorch/TensorFlow/scikit-learn); SQL for feature and data work; deploying ML workloads on AWS (SageMaker, Bedrock, Lambda, S3).

•       LLM / GenAI, RAG, prompt engineering, vector databases.

•       MLOps tooling (MLflow, Kubeflow, model registries).

•       Healthcare data and clinical NLP experience.

•       MLE with python, databricks, AWS, sql, nlp

•       Deep knowledge of Claude Code customization techniques and tools, excellent agentic prompting skills, security-first mindset, AWS Bedrock + Agentcore experience, excellent stakeholder management (bridging engineering and business) 

•       Nice To Have: LiteLLM gateway experience, cloud-based coding agent workflows, strong regression and integration testing experienc, developer experience-focused background

•       Vetting for Agentic Prompting: Ensure candidates have built loop-based coding workflows (e.g., automated error-correction loops, regression testing hooks for AI-generated code) rather than just standard single-turn LLM chat prompts. 

•       Vetting for LiteLLM & Security: The candidate must show they have built proxy architectures that enforce security guardrails, manage API keys, and load-balance across AWS Bedrock endpoints

Key Skills

Education

Bachelor's degree