Manager, GenAI AWS Platform Engineering

Johnson & Johnson

Confirmed live yesterday High trust
Closes in 4 days

Quick summary

Work type
On-site
Location
Raritan, NJ
Salary
$102,000–$177,100 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday
Closes
Sep 21, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $208k
This role $140k
$85k most similar roles pay here $263k

This role pays less than 94% of similar roles. Most pay $168,975–$246,150 — the shaded band above. At the midpoint, this role pays about $140k versus about $208k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 55 open roles on FindRole.

Listed pay typically runs $117,000–$201,250 across 48 roles with salary data.

Most-posted roles

View all roles at Johnson & Johnson

At a glance

TL;DR · Manager, GenAI AWS Platform Engineering

Manager, GenAI AWS Platform Engineering leads the modernization of the enterprise Generative AI platform on Amazon Web Services for the Technology Services team. This role involves transitioning GenAI capabilities from custom-built infrastructure to cloud-native services while ensuring governed consumption in a regulated environment. The manager oversees the engineering of the AWS foundation, including Bedrock, landing zones, multi-account architecture via Organizations and Control Tower, and networking components like VPC, PrivateLink, and Transit Gateway. Key responsibilities include defining reference architectures, managing migration waves, and delivering GxP-qualified infrastructure. The role requires expertise in Terraform, CDK, ECS, EKS, Lambda, Step Functions, DynamoDB, and S3. Additionally, the manager oversees cost, performance, and reliability engineering while leading a team of engineers to maintain consistent foundational primitives across multi-cloud environments including Azure.

What you'll do

  • Lead the modernization of the enterprise Generative AI platform by migrating services from custom infrastructure to AWS cloud-native services.
  • Define and enforce a "cloud-native-by-default" reference architecture using managed services like Amazon Bedrock, Step Functions, and Lambda.
  • Engineer the AWS foundation including multi-account architecture, landing zones, networking, and identity management in a regulated environment.
  • Codify the entire infrastructure estate as code using Terraform and CDK to eliminate manual console changes.
  • Execute seamless migration waves for existing services using blue-green cutovers and backward-compatible APIs.
  • Deliver GxP-qualified AWS infrastructure that meets strict regulatory requirements and internal security guardrails.
  • Manage cloud costs, performance, and reliability through capacity planning, multi-region design, and proactive monitoring.
  • Lead, coach, and develop a team of engineers while managing the AWS partnership and cross-cloud alignment with Azure.

What we're looking for

  • Minimum 8 years of experience in cloud infrastructure or platform engineering.
  • Minimum 2 years of formal people-leadership experience managing engineers.
  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical discipline; Master's or Ph.D. (preferred).
  • Hands-on ownership of an enterprise-scale AWS estate including multi-account architecture and landing zone design.
  • Proven experience delivering infrastructure through Infrastructure as Code using Terraform and AWS CDK.
  • Experience engineering cloud infrastructure in regulated environments such as GxP, SOX, or other audited control frameworks.
  • Practical experience supporting AI, machine learning, or Generative AI workloads on AWS.
  • AWS certifications such as Solutions Architect Professional, DevOps Engineer Professional, or Machine Learning Specialty (preferred).

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