Sofware Development Manager, Ring Agent Platforms

Amazon
Hawthorne, CA, USA2026-05-05ONSITE

About the job

We are looking for a Manager of Software Development to lead a team of engineers building a multi-agent AI platform. This platform enables organizations to design, compose, and deploy autonomous AI agents that collaborate with each other and with humans to execute complex workflows — from code generation and analysis to decision-making and task orchestration across enterprise systems.

Responsibilities

Own the delivery of this platform

Build and mentor a high-performing team of software developers

Collaborate with product and engineering partners to push the boundaries of what multi-agent systems can do in production

Qualifications

Minimum

3+ years of engineering team management experience

7+ years of working directly within engineering teams experience

3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience

8+ years of leading the definition and development of multi tier web services experience

Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations

Experience partnering with product or program management teams

Preferred

Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy

Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

Familiarity with at least one agentic AI development IDE

Familiarity with Strands Agents, Amazon Bedrock, and Bedrock AgentCore

Understanding of multi-agent patterns (swarm, graph, workflow) and the A2A protocol

Familiarity with evaluation of LLMs and AI agents

Knowledge of responsible AI practices and the use of guardrails

Familiarity with observability and debugging within AI platforms