Senior AI Platform Engineer

Senior AI Platform Engineer

2-3 days in office Boston MA

• As a Senior AI Platform Engineer you will help design build and operate the platform that powers Client agentic AI capabilities within our AWS ecosystem.
• You will work on the systems that expose client content and tools to large language models including Model Context Protocol (MCP) servers Amazon Bedrock AgentCore Gateway and Runtime retrieval and search pipelines and the knowledge and context graphs that ground model output in trusted data.
• Working alongside data scientists data engineers and DevSecOps teams you will turn research prototypes into reliable secure and scalable production services contributing automation that accelerates delivery while meeting the platforms Non-Functional Requirements (NFRs) for security performance and cost.
• This is a remote contract engagement within a distributed agile environment.

What Youll Do (Primary Responsibilities):

• Design build and maintain MCP servers that expose client content and tools to AI agents and partner integrations across AWS environments.
• Implement and operate Amazon Bedrock AgentCore Gateway and Runtime workloads including tool registration authentication and authorization patterns and dispatcher-based routing.
• Build and optimize search and retrieval pipelines including retrieval-augmented generation (RAG) architectures relevance tuning and evaluation harnesses.
• Develop knowledge and context graphs that model relationships across content and ground LLM responses in authoritative sources.
• Apply infrastructure-as-code (AWS CDK Terraform CloudFormation) to automate provisioning of AI platform infrastructure.
• Implement CI/CD automation for packaging testing deployment and observability of AI services using DevSecOps best practices.
• Define and automate monitoring alerting and evaluation strategies for deployed AI workloads.
• Ensure AI platform infrastructure meets enterprise security compliance and governance standards including supply chain hardening and per-tenant isolation.
• Partner with data scientists and product teams to operationalize new agentic capabilities and partner connectors.
• Participate in code reviews and knowledge sharing and contribute to documentation and reusable patterns.

Your Team:

This engagement is part of the Data & AI organization focusing on the AI platform that delivers agentic and retrieval-based capabilities within AWS. Areas of specialty include:

• MCP server design partner connectors and tool integration
• Amazon Bedrock AgentCore Gateway and Runtime operations
• Search retrieval and RAG architecture and evaluation
• Knowledge and context graph modeling and grounding
• Secure compliant and scalable AI platform infrastructure

About You:

• 6 years of professional experience in software data or AI/ML engineering.
• 3 years of direct experience building and operating production services on AWS.
• Strong proficiency in Python and solid software engineering fundamentals (testing code review version control).
• Hands-on experience with AWS services (Bedrock Lambda ECR S3 API Gateway IAM CloudWatch).
• Experience designing and integrating APIs or services that expose data and tools to client applications.
• Working knowledge of LLM application patterns such as retrieval-augmented generation prompt orchestration and tool use.
• Solid understanding of CI/CD and containerization (Docker).
• Experience building CI/CD pipelines (GitHub Actions Jenkins or similar).
• Experience with infrastructure-as-code (AWS CDK Terraform or CloudFormation).
• Strong communication and collaboration skills across multidisciplinary teams.
• Ability to ramp quickly and deliver independently within an existing architecture and codebase.

What Sets You Apart:

• Hands-on experience with the Model Context Protocol (MCP) or comparable agent tool-integration frameworks.
• Experience with Amazon Bedrock AgentCore Gateway or Runtime.
• Experience with knowledge graphs context graphs or graph databases.
• Experience building or tuning search and retrieval systems and evaluation pipelines.
• Experience with AWS CDK and GitHub Actions.
• Familiarity with AI governance evaluation and compliance frameworks.
• Experience with supply chain security and multi-tenant cost attribution at scale.
• Contributions to open-source AI platform MCP or DevOps tooling.