Senior Application Engineer
Bristol Myers Squibb
3 hours ago
Remote friendly (Cambridge, MA)
United States
IT
Summary
As a Senior Application Engineer (AI Venture Studio delivery team), you will build secure cloud-hosted applications (including agentic AI products and knowledge/context infrastructure). You will design APIs, services, infrastructure patterns, deployment pipelines, semantic-layer evolution patterns, and agent runtimes to support fast-moving AI Accelerator pods with reliability, observability, security, and enterprise alignment.
Key Responsibilities
- Design, build, and operate backend services/APIs powering AI Accelerator products.
- Develop integrations using Python/FastAPI or TypeScript/Node with LLM APIs, retrieval systems, workflow engines, and enterprise systems.
- Execute 6 two-week sprint cycles over 12 weeks to build/test/validate MVP increments.
- Build MCP/FastMCP services (read/write/search) for governed structured knowledge assets (e.g., markdown/YAML) with audit trails and access controls.
- Implement secure authn/authz (BMS SSO/Cloud Creds), secrets management, validation, and safe service boundaries.
- Build agentic workflows (LangGraph), retrieval/memory/context services (AWS-aligned data stores), and evolve semantic layers for SQL/NL-to-code.
- Create CI/CD, automated tests, IaC, observability/evaluation (e.g., LangSmith), quality/security gates, and sandboxed execution environments.
Qualifications
- BS+ in CS/Engineering/Science or related.
- 5+ years software/cloud/platform/backend engineering.
- AWS-native cloud-native development; Python/FastAPI or TypeScript/Node.
- CI/CD, containers, GitHub workflows, automated testing, IaC (Terraform/AWS CDK/CloudFormation).
- LLM/RAG/agentic AI experience (LangGraph/LangChain/PydanticAI, etc.).
- MCP/FastMCP, permissioned knowledge stores, vector DBs/knowledge graphs, evaluation-driven development.
- SQL/semantic layers; provenance/audit/access-control patterns.
- Frontier LLM integration via enterprise channels (OpenAI/Anthropic/Gemini/Bedrock).
- Experience with AI-assisted dev tools (e.g., GitHub Copilot).
Application Instructions
- If interested but not a perfect match, apply anyway.
Benefits (explicitly listed)
- Health coverage (medical/pharmacy/dental/vision), wellbeing programs, 401(k), disability/life insurance; paid time off (flexible time off or vacation based on location/eligibility).
As a Senior Application Engineer (AI Venture Studio delivery team), you will build secure cloud-hosted applications (including agentic AI products and knowledge/context infrastructure). You will design APIs, services, infrastructure patterns, deployment pipelines, semantic-layer evolution patterns, and agent runtimes to support fast-moving AI Accelerator pods with reliability, observability, security, and enterprise alignment.
Key Responsibilities
- Design, build, and operate backend services/APIs powering AI Accelerator products.
- Develop integrations using Python/FastAPI or TypeScript/Node with LLM APIs, retrieval systems, workflow engines, and enterprise systems.
- Execute 6 two-week sprint cycles over 12 weeks to build/test/validate MVP increments.
- Build MCP/FastMCP services (read/write/search) for governed structured knowledge assets (e.g., markdown/YAML) with audit trails and access controls.
- Implement secure authn/authz (BMS SSO/Cloud Creds), secrets management, validation, and safe service boundaries.
- Build agentic workflows (LangGraph), retrieval/memory/context services (AWS-aligned data stores), and evolve semantic layers for SQL/NL-to-code.
- Create CI/CD, automated tests, IaC, observability/evaluation (e.g., LangSmith), quality/security gates, and sandboxed execution environments.
Qualifications
- BS+ in CS/Engineering/Science or related.
- 5+ years software/cloud/platform/backend engineering.
- AWS-native cloud-native development; Python/FastAPI or TypeScript/Node.
- CI/CD, containers, GitHub workflows, automated testing, IaC (Terraform/AWS CDK/CloudFormation).
- LLM/RAG/agentic AI experience (LangGraph/LangChain/PydanticAI, etc.).
- MCP/FastMCP, permissioned knowledge stores, vector DBs/knowledge graphs, evaluation-driven development.
- SQL/semantic layers; provenance/audit/access-control patterns.
- Frontier LLM integration via enterprise channels (OpenAI/Anthropic/Gemini/Bedrock).
- Experience with AI-assisted dev tools (e.g., GitHub Copilot).
Application Instructions
- If interested but not a perfect match, apply anyway.
Benefits (explicitly listed)
- Health coverage (medical/pharmacy/dental/vision), wellbeing programs, 401(k), disability/life insurance; paid time off (flexible time off or vacation based on location/eligibility).