Senior Application Engineer

Bristol Myers Squibb

. Design, build, and operate backend services, APIs, and application components that power AI Accelerator products.

Posted 5/22/2026full-timeSeattle • Massachusetts, New Jersey, Washington • 🇺🇸 United StatesSenior💰 $137,530 - $183,319 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudNode.jsPostgresPythonRedisSQLTerraformTypeScript

About the role

Key responsibilities & impact

Design, build, and operate backend services, APIs, and application components that power AI Accelerator products.
Develop Python/FastAPI, TypeScript/Node, or similar services that integrate LLM APIs, retrieval systems, workflow engines, and internal enterprise systems.
Execute AI Accelerator cycles of six two-week sprints over a 12-week cycle by developing, testing, and validating cloud and agentic AI product increments.
Develop MCP-accessible services that allow approved agents to read, write, search, and maintain structured (e.g. markdown/YAML) knowledge assets.
Build MCP/FastMCP read-write-search APIs, permissioned knowledge stores, version control, audit trails, access controls, and integrations with AWS-native storage and identity patterns.
Implement secure application patterns for authn/authz, BMS SSO, BMS Cloud Creds, secrets management, auditability, input validation, and safe service boundaries.
Partner with frontend engineers to define clean API contracts, streaming response patterns, error handling, and service-level behaviors for AI-powered user experiences.
Build and host agentic workflows using LangGraph, including workflow state, multi-agent orchestration, tool execution, fan-out/fan-in patterns, and durable checkpoints.
Develop MCP tool integrations and FastMCP servers that allow agents to use governed enterprise capabilities safely and consistently.
Implement retrieval, memory, and context services using AWS-aligned data stores such as S3, Athena, PostgreSQL/RDS, ElastiCache/Redis, OpenSearch, Amazon S3 Vectors, and Amazon Neptune.
Build and evolve the semantic layer for SQL and other natural-language-to-code generating agents, enabling novel analytical questions to be grounded in query history, column values, warehouse context, explicit instructions, memory, and governed data tools.
Create and maintain CI/CD pipelines, environment configuration, automated tests, infrastructure-as-code, and release processes for cloud AI applications.
Instrument application reliability, latency, cost, usage, tracing, and model/agent behavior using enterprise observability and AI evaluation tools such as LangSmith or similar platforms.
Embedding automated quality gates, security scans, regression tests, structured output validation gates, and responsible AI guardrail checks into delivery pipelines.
Continuously improve shared platform patterns based on lessons learned across pods, changing enterprise standards, and advances in AI engineering practices.
Partner with AI Engineers, Data Engineers, Data Scientists, Frontend Engineers, Pod Leads, architects, and product teams to solve complex delivery challenges.
Help complete MVP transition activities by maturing AI capabilities, adding key features, validating reliability in practice, confirming business value, and assessing production readiness.
Provide technical coaching through design reviews, code reviews, architecture reviews, incident learning, documentation, and reusable examples.

Requirements

What you’ll need

Bachelor's or higher degree in Computer Science, Engineering, Science, or a related field.
5+ years of experience in software engineering, cloud engineering, platform engineering, or backend application development with increasing responsibility.
Hands-on experience building cloud-native applications on AWS; familiarity with services such as S3, RDS/PostgreSQL, Athena, ElastiCache/Redis, OpenSearch, Fargate, Lambda, IAM, and VPC patterns.
Strong proficiency in Python, FastAPI, TypeScript/Node, or comparable backend application frameworks.
Experience with containers, CI/CD, GitHub-based workflows, automated testing, environment configuration, and infrastructure-as-code such as Terraform, AWS CDK, or CloudFormation.
Experience building LLM, RAG, or agentic AI applications using frameworks such as LangGraph, LangChain, PydanticAI, Claude Agent SDK, or similar tools.
Familiarity with MCP/FastMCP, read-write-search APIs, permissioned markdown/YAML stores, vector databases, knowledge graphs, session/state management, structured output validation gates, and evaluation-driven development.
Experience with SQL, semantic layers, data warehouse context, query history, and systems that translate LLM-derived meaning from unstructured scientific or operational sources into governed data/context layers.
Experience building sandboxed execution, data branching, provenance, version control, audit, and access-control patterns for agentic or data-intensive applications.
Practical experience integrating with model providers and a variety of approved frontier LLM models through enterprise AI services such as OpenAI, Anthropic, Gemini, AWS Bedrock, or similar approved channels.
Effective use of coding agents or AI-assisted development tools such as Claude Code, Codex, Gemini CLI, GitHub Copilot, or similar tools.
Excitement for experimenting with the latest AI tools and technologies while turning frontier prototypes into reliable foundations that help discover, develop, and deliver innovative medicines.
Curious and inquisitive mindset, with strong communication skills and comfort operating in fast-moving, cross-functional agile teams.

Benefits

Comp & perks

Health Coverage: Medical, pharmacy, dental, and vision care.
Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
Work-life benefits include: Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonFastAPITypeScriptNodeAWSSQLCI/CDinfrastructure-as-codeLangGraphautomated testing

Soft Skills

communicationcuriositycollaborationproblem-solvingtechnical coachingagile mindsetinquisitive mindsetleadershipadaptabilitycritical thinking

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in EngineeringBachelor's degree in Science