AI Platform Engineer

📋 Description Build and run the MCP fleet — ship, secure, and patch self-hosted and managed MCP servers for Own the agent platform other teams build on — the deploy pattern, guardrails, observability, and Co-own the Bedrock runtime and gateway — model access, cost attribution, content-filtering Make AI spend and usage visible — build the Bedrock-to-Snowflake pipeline, identity-matched, with Make the secure path the easy path — own MDM config, desktop client setup, credentials, and auth Build governance into the platform — route workflows by data sensitivity, enforce least privilege 🎯 Requirements 6+ years in software engineering, platform engineering, or DevOps, including ownership of something Hands-on AWS — IAM, ECS or Lambda, CloudWatch, and working VPC knowledge. Full-stack range — backend services, APIs, CI/CD, and containerized deployments. Builder mindset — can write an MCP server or API integration from scratch. Hands-on with LLMs — comfortable with LLM APIs, prompt engineering, and agent development. Self-direction — can take an underspecified task and figure out all the parts. 🎁 Benefits Extra days off to avoid burnout and maintain well-being. 401(k) Retirement Savings Plan with a 3% employer match. Maternity and Parental Leave. Mental health support for you and your family through the Modern Health app. Full health benefits package for you and your family.