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# Sr Software Dev Engineer, AI Agent Identity & Governance, AWS Applied AI Solution - Core Services

- **Company:** Amazon.com, Inc.
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $168,100.0 - $227,400.0
- **Contract:** Internship / Graduate position
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Software, Code Review, Computer Programming, Data Masking, Software Design Patterns, Distributed Systems, Identity and Access Management, Knowledge Management, Open Source Technology, Software Product Management, Azure Machine Learning, Software Engineering, Large Language Models, Prompt Engineering, Generative AI, Information Technology, Build Process, Machine Learning Operations, Virtual Agents, Api Design, Software Coding, Software Version Control, Programming Languages
- **Published:** August 11, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/27920317/Sr-Software-Dev-Engineer-Ai-Agent-Identity-Governance-Aws-Applied-Ai-Solution-Core-Services-Washington-Seattle-7375

## About the Role

5+ years of non-internship professional software development experience

 - 5+ years of programming with at least one software programming language experience
 - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
 - Experience as a mentor, tech lead or leading an engineering team
 - Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
 - Experience designing and implementing AI/ML systems, including working with LLMs, prompt engineering, retrieval augmented generation (RAG), fine-tuning, or AI agent development
 - Proven track record building distributed systems with well-designed APIs that operate reliably at enterprise scale
 - Demonstrated ability to create reusable software components with clean interfaces that can be leveraged by multiple teams
 - Strong working knowledge of AWS AI/ML services such as Amazon Bedrock, SageMaker, and related infrastructure
 - Successful history of cross-organizational collaboration, driving technical convergence while maintaining delivery velocity, 10+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
 - Bachelor's degree in computer science or equivalent
 - Expertise in PII handling and data protection, with knowledge of data masking techniques, de-identification methodologies, and regulatory compliance frameworks for managing sensitive information in AI systems
 - Experience designing sophisticated authorization frameworks featuring fine-grained permission models that support delegation, just-in-time approval workflows, and clear attribution between human and AI agent actions

## Description

Lead our pioneering AI initiative at AWS and define the future of AI agents. Shape how businesses leverage artificial intelligence by creating foundational building blocks used across AWS business applications.

The Core Services team within AWS Applied AI Solutions is creating the foundations that will power the next generation of AI agents from small business to enterprise scale. As a technical leader, you'll lead our new agentic AI building blocks initiative, pioneering the development of reusable AI components that accelerate and standardize AI product delivery across AWS business applications such as contact center, supply chain, healthcare and life sciences. You'll own one critical capability area such as agent identity and governance, agent collaboration & orchestration, agent evaluation, or knowledge management, and have the privilege to define what we build and how we build it.

This role combines the excitement of a startup environment with the scale of AWS. You'll research state-of-the-art open source and internal tools, tackle highly ambiguous problems, and lead a team building a V1 product from the ground up. You won't just be implementing someone else's vision - you'll chart the course, define the roadmap, and create solutions that eliminate non-differentiating work while ensuring enterprise-grade quality and consistency. If you thrive on ownership, are passionate about AI, and want to fundamentally influence how AWS builds AI products, this role offers an extraordinary opportunity to make your mark., Own the technical architecture and strategy for a critical AI agent capability area, setting the foundation for enterprise-scale AI solutions across AWS

 - Lead projects requiring multiple engineers, balancing business goals with technical excellence while navigating ambiguous problem spaces
 - Research, evaluate, and integrate state-of-the-art AI technologies, making informed decisions about build vs. leverage approaches
 - Design and implement reusable AI components that meet enterprise-grade quality standards while simplifying complex technical challenges
 - Drive consensus across teams with different priorities and perspectives to create unified AI building blocks
 - Champion engineering best practices, establishing a culture of robust software development with exemplary code organization, clarity, and maintainability
 - Mentor and coach other engineers, fostering technical growth while creating an environment where your team thrives independently
 - Communicate complex technical designs to diverse audiences, from engineers to non-technical stakeholders and senior leadership

A day in the life
Your morning starts with an engineering team standup, followed by collaborative sessions with product managers in your team to provide requirement and internal customer inputs. You'll dedicate focused time to researching the latest AI agent techniques and designing reusable, scalable building blocks for your capability area. Throughout the day, you'll work with engineers and scientists within your team to implement solutions, leveraging coding agents to write and test code more efficiently. You might lead a technical design review with scientists, engineers, product managers, solution architects from across Applied AI Solutions, gathering diverse perspectives to strengthen your approach. Your day could include architecture, prompt, component, API design work, meeting with internal customers to understand their AI agent needs, or presenting your vision to leadership stakeholders.


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