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Senior Manager, Content & Digital Experience Capabilities – Solution Architecture & Engineering

Bristol Myers Squibb

Princeton, NJ, US$140k – $169konsite

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About this role

Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us .

Key Responsibilities:

• Architect, build, and deliver solution architectures for content & digital platforms and the Marketing AI platform — hands-on writing production-grade backend code (Python, Node.js), APIs (REST/ GraphQL ), data pipelines, and infrastructure-as-code.  

• Serve as   Technical Lead for   the end-to-end Azure-to-AWS migration of the Marketing AI platform — including service mapping, data migration, workload re-platforming, and   cutover —   and design the target-state AWS architecture using Bedrock, SageMaker, Lambda, Step Functions, ECS/EKS, API Gateway, DynamoDB, and   EventBridge .  

• Build and deploy agentic AI applications — autonomous marketing agents for content generation, audience segmentation, campaign orchestration, and real-time personalization — using frameworks such as   LangChain ,   LangGraph ,   CrewAI , or custom orchestration, with proper governance including human-in-the-loop checkpoints and responsible AI practices.  

• Support   the north-star vision of automating end-to-end marketing   workflows   working with the   Marketing AI & Innovation Engineering Lead   — from insight generation and content creation through approval, distribution, channel activation, and performance measurement — to increase speed-to-market and enable personalized marketing at scale.  

• Drive   DevOps and cloud infrastructure — design and maintain CI/CD pipelines (GitHub Actions,   CodePipeline , Jenkins), manage Infrastructure-as-Code (Terraform, CDK/CloudFormation), container orchestration (ECS/EKS/Kubernetes), serverless deployments, environment strategy (dev/staging/prod), and enforce best practices for automated testing, blue/green deployments, monitoring, logging, and incident response.  

• Ensure platform security, compliance, and cost optimization — hands-on with IAM, secrets management, VPC/network security, encryption, and data privacy controls;   monitor   resource   utilization , implement auto-scaling, right-size compute, and   establish   cost governance.  

• Lead full-stack and backend engineering — design and build microservices, event-driven architectures, database solutions (PostgreSQL/RDS, DynamoDB/ DocumentDB ), data pipelines (AWS Glue,   PySpark , Airflow), and AI/ML pipelines (SageMaker, Bedrock); build frontend components (React.js, TypeScript) as needed.  

• Implement robust integration patterns connecting the Marketing AI platform and content/digital platforms with the broader ecosystem (Veeva, AEM, DAM, CRM, CDP, analytics tools) via APIs, event streams, and middleware such as MuleSoft or   webMethods .  

• Lead   PoCs   and pilots—from ideation to working prototype—for agentic marketing use cases (e.g., AI-driven personalization, automated MLR pre-checks, intelligent content repurposing), and scale successful pilots to production.  

• Lead by example — actively contributing code, conducting architecture reviews, pair-programming, and providing hands-on technical mentorship to elevate team engineering quality and   maintain   alignment with architectural standards and best practices.  

• Manage technical roadmaps, architecture documentation, and CLAD processes — ensure phased delivery with minimal business disruption, clear rollback strategies, and measurable success criteria; drive continuous improvement for productivity, cost savings, and engineering velocity.  

• Partner cross- functionally   with   CASA   Leads, C-BI&T, Cloud Engineering, Cyber Security, Data & Enterprise Architecture, vendor partners, and agency teams to ensure successful delivery across all content, digital, and AI capabilities .  

Required Qualifications   & Experience   

• Bachelor's or   Master's degree in Computer Science   or a related field with   8 +   years of hands-on IT engineering and architecture experience, including   6 + years in a hands-on technical architect / lead engineer role for content, digital, and/or AI platforms.  

• 4-5   years of heavy backend engineering—building production-grade APIs, microservices, event-driven systems, and data pipelines using Python, Node.js, or Java.  

• 4-5   years of hands-on DevOps and AWS cloud infrastructure—CI/CD pipeline design, Infrastructure as Code (Terraform, CDK/CloudFormation), container orchestration (ECS/EKS/Kubernetes), serverless architectures, and environment management—with demonstrated experience in cloud migration (Azure-to-AWS preferred) and/or AI/ML platform development.  

• Strong full-stack capabilities—backend and DevOps as core strengths—with working   proficiency   in frontend (React.js, JavaScript/TypeScript) and hands-on experience with both relational (PostgreSQL, RDS) and NoSQL databases (DynamoDB,   DocumentDB ).  

• Experience with AI/ML and GenAI - Amazon Bedrock, SageMaker, LLM-based application development, prompt engineering, RAG, and agentic AI frameworks ( LangChain ,   LangGraph ,   CrewAI , or similar).  

• Strong understanding of IT governance processes including data architecture, data privacy, cyber security reviews, risk assessments, Git-based workflows, and

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