Core Java and Full Stack Application Developer QMS Developer

Job Title : Senior AI Software Engineer – QMS Developer

Location : Sunnyvale, CA - Fully onsite (5 days)

Duration : 1 year

W2 Candidate Only

Top Skills:

• Strong core Java and full-stack application development in validated GxP environments (Spring Boot, REST APIs, SQL, modern front-end framework)
• Python-based AI engineering — LLM application and agent development (RAG, prompt engineering, orchestration, evaluation)
• AWS solution architecture for AI and application workloads (Bedrock/SageMaker, Lambda, API Gateway, ECS, S3, IAM, VPC)
• Systems integration and API/web service development against enterprise QMS platforms
• GxP / 21 CFR Part 11 / GAMP 5 computer system validation experience .

Detailed Job description:

Position Overview:

This is a software engineering role focused on building applications and AI capabilities for our regulated quality systems landscape. The person will design and develop Java-based applications, services and integrations that support GxP processes, and will design, build and support Python-based AI agents that automate and augment those same processes.

The emphasis of this role is engineering, not platform configuration. We are looking for a strong developer who can write production Java and Python, design solutions on AWS, and do so inside a validated environment. Familiarity with an enterprise QMS such as TrackWise is important context, but deep configuration expertise is not the primary requirement, the ability to build, integrate and support software around it is.

Roles and Responsibilities:

Application Development — GxP Systems

• Design, develop, test and deploy Java-based applications, microservices and REST APIs supporting quality, compliance and post-market processes
• Build full-stack components — Spring Boot services, data access layers and front-end screens — including user interfaces that present AI-generated recommendations to quality reviewers
• Develop integrations and web services between the QMS platform and surrounding enterprise systems, including outbound/inbound web services and event-driven interfaces
• Write and maintain unit, integration and automated regression tests; participate in code review and manage source control, branching and release processes
• Troubleshoot and resolve production defects across application, integration and database layers

AI Engineering

• Design, develop, deploy and support LLM-based agents in Python that assist quality processes .
• Build and tune RAG pipelines, prompt templates, evaluation harnesses and guardrails; measure agent accuracy, drift and regression against defined acceptance criteria
• Integrate agent outputs into quality workflows through APIs, including human-in-the-loop review, confidence thresholds, fallback behaviour and full capture of the audit trail
• Take ownership of an existing AWS hosted AI framework post-implementation, including production support, enhancement and new agent development
• Establish monitoring and observability for AI components  quality metrics, latency, token cost and failure modes

Architecture, Integration and Compliance

• Design and document AWS architecture for AI and application workloads Bedrock and/or SageMaker, Lambda, API Gateway, ECS, S3, IAM and VPC-based network design
• Partner with architecture review, security review and infrastructure groups to get designs approved and deployed
• Produce technical specifications, process flows, functional and technical design documentation
• Perform solution design, requirements definition, testing and validation support through implementation
• Comply with regulatory, computer system validation and change control requirements; produce the associated validation deliverables
• Work with process owners to identify continuous improvement and automation opportunities, and recommend solutions using system stan