Manager, GenAI AWS Platform Engineering

• Job title Manager, GenAI AWS Platform Engineering
• Function Technology Product & Platform Management
• Sub function Intelligent Automation Engineering
• Category Principal Engineer, Intelligent Automation Engineering (ST7)
• Location Raritan / United States of America
• Date posted Sep 14 2026
• Requisition number R-097988
• Work pattern Hybrid Work

This job posting is anticipated to close on Sep 21 2026. We may however extend this time period, in which case the posting will remain available on www.careers.jnj.com to accept additional applications.

Description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

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Job Description:

J&J is currently seeking a Manager, GenAI AWS Platform Engineering for their Technology Services team based in Raritan, NJ.

The Manager, GenAI AWS Platform Engineering leads the modernization of Johnson & Johnson's enterprise Generative AI platform on Amazon Web Services. The primary objective of this role is optimize the governed consumption of GenAI/Agentic AI capabilities on the AWS cloud as well as re-platforming: moving GenAI capabilities off bespoke, custom-built infrastructure and onto AWS cloud-native services. You are the accountable engineering leader for that transition — deciding what is replaced by an AWS-native service, what is retired, what must remain custom and why — and for engineering the AWS foundation the modernized platform runs on: Amazon Bedrock, the landing zone and multi-account architecture on AWS Organizations and Control Tower, and the networking, IAM, VPC and PrivateLink design that keeps GenAI traffic on private paths.

This is engineering around AWS cloud-native capability, in a regulated setting. You set the reference architecture that defines the AWS-native way to build on this platform, run the migration waves that move existing services onto it, hold the standard that new capability is built cloud-native by default, and deliver GxP-qualified AWS infrastructure so regulated GenAI workloads can run there. You lead a team of AWS platform engineers and the AWS agentic engineering capability, and you work with the Azure platform engineering sub-team to keep foundational primitives consistent across clouds without forcing uniformity where each hyperscaler is genuinely better. You will stay ahead of new capabilities and changes to insure constant modernization and evolution. Our Credo grounds how you lead: an inclusive work environment where each person is considered as an individual, diversity and dignity are respected, and merit is recognized.

This position will report into the Senior Manager, TS GenAI platform engineering.

Key Responsibilities:

· Own the GenAI cloud-native modernization roadmap on AWS: assess each service against its managed equivalent, decide replace, refactor, retain or retire, and re-platform onto Bedrock, AgentCore, ECS and EKS, Lambda, Step Functions, DynamoDB and S3.

· Define the AWS Well-Architected reference architecture and enforce a cloud-native-by-default standard, favoring managed orchestration — harness engineering and durable workflow on Step Functions — over bespoke agent development.

· Engineer the AWS foundation: Bedrock access and quotas; the landing zone and multi-account architecture on Organizations and Control Tower; VPC, PrivateLink, Transit Gateway and least-privilege IAM — delivered for standardized consumption with the Cloud and ISRM teams.

· Codify the estate as Infrastructure as Code in Terraform and CDK — modules, pipelines, drift detection, policy-as-code — replacing console changes, contributing hands-on where needed.

· Run migration waves without disrupting users: Route 53 weighted and blue-green cutover, backward-compatible APIs, data migration, documented rollback, and decommissioning only once the AWS replacement is proven in production.

· Deliver GxP-qualified AWS infrastructure under change control agreed with Quality and ISRM, and partner with GenAI governance on guardrail, identity and traceability controls that reduce dependency on manual review.

· Engineer the hosting substrate for the enterprise platform capabilities — APIM, Content Sphere, Agent Framework, Drafting Assist, the MCP Gateway and the Agent, Skills and MCP catalog — plus the semantic layer, retrieval and evaluation harness services that agentic and application workloads build on.

· Own cost, performance and resilience engineering: tagging and showback, commitment discounts, Bedrock inference efficiency, multi-AZ and multi-region design, capacity planning and disaster recovery — with CloudWatch and X-Ray observability and reporting on adoption, reliability and cost.

· Lead, coach and develop the AWS platform engineering team in an inclusive, Credo-grounded environment — accountable for timely delivery, budget optimization and engineering quality, and supporting LFRP planning.

· Own the AWS partnership and cross-cloud alignment: architecture reviews, early access and quota negotiation; position papers on emerging capabilities; adoption of agentic approaches in software development; and parity with the Azure platform engineering sub-team on shared primitives.

Qualifications:

· Minimum of 8 years of progressive experience in cloud infrastructure or platform engineering, including at least 2 years of formal people-leadership experience managing engineers, or demonstrated equivalent leadership of engineering teams.

· Bachelor's degree in Computer Science, Engineering, Information Technology or a related technical discipline is required; a Master's degree or a Ph.D. is preferred.

· Demonstrated hands-on ownership of a production AWS estate at enterprise scale, including multi-account architecture, landing zone design and the operational reality of running it.

· Proven experience delivering infrastructure through Infrastructure as Code as the primary interface, with a track record of eliminating manual console changes in favor of reviewed, versioned code.

· Experience engineering cloud infrastructure in a regulated environment — GxP, validated systems, or an equivalent regime such as SOX or a comparable audited control framework — and producing evidence that satisfies auditors.

· Practical experience supporting AI, machine learning or Generative AI workloads on AWS, including the networking, identity and capacity considerations specific to managed inference services.

· Demonstrated ability to manage cloud cost and performance as engineering problems, with specific examples of architectural changes that improved efficiency without degrading service.

· Experience working directly with a hyperscale cloud provider's account and solutions-architecture teams to influence quotas, service adoption and roadmap alignment.

· Ability to communicate infrastructure trade-offs clearly to both engineers and non-technical stakeholders, including Quality, Security and business partners.

· Experience coaching senior individual contributors and supporting their technical growth without taking over their technical decisions.

Required Skills:

· Cloud-native modernization and re-platforming: assessing custom-built services against managed AWS alternatives and sequencing migration waves

· AWS Organizations, Control Tower, service control policies and multi-account landing zone design for regulated workloads

· Amazon Bedrock platform configuration: model access, inference profiles, provisioned throughput, service quotas and private endpoints

· AWS cloud-native compute and data services — ECS and EKS, AWS Lambda, Step Functions, DynamoDB, S3 and API Gateway, including harness and benchmark environments built on them

· Semantic layer and governed data access patterns on AWS, including Bedrock Knowledge Bases, Athena or Glue catalog integration, exposing enterprise data to models without copying it

· AWS networking — VPC and subnet architecture, PrivateLink and VPC endpoints, Transit Gateway, Route 53 and egress control

· AWS IAM in depth — role and trust policy design, permission boundaries, least privilege, cross-account access and identity federation

· Infrastructure as Code with Terraform and AWS CDK, including module design, state management, policy gates and CI/CD delivery

· Migration engineering — dual-run and cutover planning, backward-compatible interfaces, data and state migration, rollback and decommissioning

· AWS cost engineering — commitment-based discounts, right-sizing, Bedrock inference cost efficiency, tagging and anomaly detection

· AWS reliability engineering — multi-Availability Zone and multi-region design, capacity planning, disaster recovery design and testing

· GxP qualification of cloud infrastructure and IaC change, with validation evidence maintained through migration

· Contractor and vendor management.

Preferred Skills:

· Experience leading a large-scale re-platform or cloud migration of an established production service, including legacy decommissioning

· Experience running Microsoft Azure alongside AWS and a practical view of where cross-cloud consistency is worth its cost

· AWS certifications such as Solutions Architect Professional, DevOps Engineer Professional or Machine Learning Specialty

· Kubernetes platform engineering with GitOps delivery, cluster lifecycle management and multi-tenancy

· Familiarity with Amazon Bedrock AgentCore sufficient to support agentic workloads on the platform

· Computer system validation for cloud infrastructure in a pharmaceutical or medical device setting

· Familiarity with Model Context Protocol and the AWS infrastructure requirements of hosting MCP servers securely

· Experience with FinOps practice for AI and inference workloads

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The anticipated base pay range for this position is :

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