Software Development Engineer, AI Ops Integration
Explicitly requires vibe coding skills—uses AI-assisted development and LLMs to rapidly prototype and iterate.
About the Role
Senior Software Development Engineer responsible for architecting and delivering production AI systems that combine LLM-powered automation, multi-agent orchestration, and scalable platform infrastructure for Amazon Operations. The role owns end-to-end design, integration, and the development-as-a-service tech stack to enable builders and automate operational workflows across transportation and fulfillment.
Job Description
Role
As a Senior Software Development Engineer on Ops AI Integration, you will own the architecture and delivery of production systems that combine LLM-powered automation, multi-agent orchestration, and scalable platform infrastructure. You will build and evolve platform components (MCP tools, AI Hub, Synapse AI platform), automate operational workflows, and shape the development-as-a-service tech stack for builders across geographies.
Key Responsibilities
- Lead technical design and architecture of production AI systems end-to-end, including data pipelines, model serving, and user-facing applications.
- Architect and build multi-agent orchestration solutions (MCP tools, AI Hub modules) to automate complex operational workflows across systems and APIs.
- Own and evolve the Synapse AI platform, designing shared infrastructure, reusable components, and user interfaces for non-technical operations users.
- Define integration architecture across internal systems, databases, and MCP servers to enable modular and scalable orchestration.
- Shape the development-as-a-service tech stack for the Forward Deployed Builders Program, creating standards, templates, and tooling.
- Drive engineering excellence across the ML lifecycle: experimentation, deployment, monitoring, evaluation, and incident response.
- Design guardrails, evaluation frameworks, and human-in-the-loop architectures to ensure safe and reliable production AI at scale.
- Partner with scientists, product managers, and operations leaders to translate ambiguous business problems into scoped technical solutions and delivery milestones.
Team
Cross-functional team of machine learning engineers, ML & AI scientists, and technical program/product managers focused on automating operational decisions in Amazon’s supply chain using a build-measure-learn cycle.
Requirements
Basic Qualifications
- Bachelor’s degree.
- Experience as a mentor, tech lead, or leading an engineering team.
- Experience leading architecture and design for reliability and scaling of systems.
- Programming experience in at least one modern language such as Java, C++, or C# with object-oriented design.
- Knowledge of machine learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques.
- Experience scripting in Python or Javascript.
- Demonstrated ability to rapidly prototype and iterate using AI-assisted development (vibe coding), leveraging LLMs and generative tools.
Preferred Qualifications
- Master’s degree in computer science or equivalent.
- Experience with full software development lifecycle (coding standards, code reviews, source control, build processes, testing, operations).
- Knowledge of system performance, memory management, and parallel computing principles.
- Experience delivering complex software systems to customers.