ML Engineer I

Role Description Focus Area Build MCP Servers for CIE (expose scoring, rules, explainability as MCP tools via Model Context Protocol), Integrate with AgentCore Gateway (JWT/mTLS authentication, entitlement checks, routing), Deploy BHI custom models to Databricks Model Serving + Snowflake (UDFs, external functions), AWS Bedrock integration for LLM explainability via AI Marketplace subscription, PHI guardrails implementation (pre-request scanning, post-response masking for healthcare data), MLflow model registry (versioning, A/B testing, rollback), Build CI/CD for model deployment, Feature store integration (Databricks Feature Store MCP tools), OpenTelemetry instrumentation (usage events emission to AI Marketplace metering), MCP tool manifest registration (score_claim, explain_detection, provider_profile tools) Skill AWS/ Databricks Certified (preferred) Python 5+ years, Familiarity with MCP Protocol (Model Context Protocol) - build MCP servers that expose tools, MLOps/MLflow 3+ years (model registry, serving) on AWS and Databricks, Databricks Model Serving production (REST API endpoints), Snowflake UDF + external function deployment, OAuth2/JWT authentication + mTLS certificate handling, AWS Bedrock (LLM integration for explainability), AgentCore Gateway integration (JWT validation, entitlement enforcement, tool routing), PHI/HIPAA compliance (pre/post-request PHI scanning), OpenTelemetry (usage event emission, distributed tracing), REST API development (MCP tool endpoints), Docker/containerization, Monitoring (Databricks, CloudWatch), Git + GitHub + CI/CD, Must have 3-5 years MLOps with AWS + Databricks + Snowflake, Must understand MCP Protocol or willingness to learn (AWS AgentCore documentation), Must have worked with OAuth2-secured APIs

Skills aws,hipaa compliance,aws databricks,json web token,rest api development,cicd,docker containerization,