Senior AI Engineer

Bristol Myers Squibb

Senior AI Engineer within Bristol Myers Squibb, responsible for building secure cloud-hosted applications. Design APIs and collaborate with teams to enhance pharmaceutical R&D and product delivery.

Posted 7/23/2026full-timeBrisbane • California, New Jersey, Washington • 🇺🇸 United StatesSenior💰 $137,530 - $183,319 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building secure cloud-native applications on AWS, with strong proficiency in Python and backend frameworks. Capable of designing APIs, CI/CD pipelines, and collaborating effectively with cross-functional teams to enhance AI capabilities.

Highest-signal resume keywords

Cloud-Native Application DevelopmentAPI Design and DevelopmentCI/CD Pipeline CreationPython ProgrammingAWS Services Familiarity

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Applicant Tracking System Keywords

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Hard Skills

PythonFastAPITypeScriptAWSTerraformSQLLangChainPydanticAIGitHub WorkflowsAutomated Testing

Soft Skills

CollaborationCuriosityProblem-Solving

Tools & Technologies

AWS LambdaOpenAIClaude CodeGitHub CopilotAWS CDKCloudFormationElastiCacheRDS/PostgreSQLFargateAthena

Industry Keywords

AI ApplicationsCloud EngineeringData EngineeringSemantic LayersAgentic AIData WarehouseVersion ControlInfrastructure as CodeKnowledge GraphsMVP Transition

Tech Stack

Tools & technologies

AWSCloudNode.jsPostgresPythonRedisSQLTerraformTypeScript

About the role

Key responsibilities & impact

As a Senior AI Engineer within Bristol Myers Squibb's AI Venture Studio team, you will be a hands-on individual contributor responsible for building secure cloud-hosted applications.
Design APIs, services, infrastructure patterns, deployment pipelines, and semantic-layer evolution patterns for agent context engineering.
Collaborate with frontend engineers to define clean API contracts, streaming response patterns, error handling, and service-level behaviors for AI-powered user experiences.
Create and maintain CI/CD pipelines, environment configuration, automated tests, and release processes for cloud AI applications.
Partner with AI Engineers, Data Engineers, Data Scientists, and product teams to solve complex delivery challenges.
Continuously refine delivery priorities and deliver MVP transition activities by maturing AI capabilities.

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.
Curiosity and excitement for experimenting with the latest AI tools and technologies while turning frontier prototypes into reliable foundations.

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.
Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays.
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.