Are you a builder who thrives in ambiguity? Do you get energized turning proof-of-concepts into production-grade AI systems, fast and with a high bar? If you want to design agentic solutions that solve real operational problems at Amazon's global scale, this role is for you.

Amazon's Ops Tech Solutions (OTS) Data ANCHOR organization is seeking a Sr. Systems Development Engineer with an AI/Solutions Architect mindset to join our solutions development, Decision Intelligence(DI) team within Anchor. You will design, build, and ship technical solutions, agentic AI automations and tools that integrate with third-party platforms (ServiceNow), first-party Amazon systems, and cross-organizational services spanning OTS.

This is not a "maintain existing systems" role. You will take ideas from whiteboard to production, building, automation to reduce KTLO burden, improve associate experience and enable speed with AI agents, MCPs (Model Context Protocols), and agentic automation systems that drive measurable impact across Amazon's worldwide operations footprint. You will be a senior technical leader on the team: raising the coding bar, establishing architectural patterns for long-term scalability, and ensuring we deploy solutions that last, not throwaway POCs.

The DI team team builds and deploys automation and agentic AI solutions that integrate with enterprise platforms and internal orchestration systems to drive operational efficiency gains at scale. Our solutions currently deliver thousands of hours in annual labor savings and operate globally, processing thousands of tickets weekly and millions of telemetry indicator. As our portfolio expands, we need a senior engineer who can own complex technical problems end-to-end and partner across data science, data engineering, and product teams to ship AI-ready solutions.

Key job responsibilities
Development & AI Solutions

• Design and build production-grade agentic AI solutions — from agent orchestration to API integrations with ServiceNow (3P) and Amazon internal systems (1P)
• Develop MCPs, agentic frameworks, and automation systems that enable scalable, reusable architectures across the Decision Intelligence portfolio
• Partner with Data Scientists and Data Engineers to productionize ML models, build AI-ready data pipelines, and develop agent capabilities (LLM orchestration, prompt engineering, RAG, tool-use patterns)
• Turn POCs into real, scalable production systems with a high quality bar — rapidly prototype, validate, and harden solutions for long-term deployment

Architecture & Integration

• Architect end-to-end systems that connect AI agents to enterprise workflows, enabling automated ticket processing, device management, and operational decision-making at scale
• Build integrations across OTS and RME ecosystems, connecting agents to multiple upstream/downstream services, data sources, and streaming platforms
• Design user-facing platforms and dashboards where AI integrations surface prescriptive recommendations to field operations partners
• Design guardrails, evaluation frameworks, and safety mechanisms to ensure production AI systems operate reliably at scale

Engineering Excellence & Operational Ownership

• Raise the engineering bar — establish coding standards, drive code reviews, define architectural patterns, and mentor team members on best practices
• Own the full development lifecycle — write design documents, implement solutions, build CI/CD pipelines, deploy to production, and monitor operational health
• Participate in on-call rotations and drive operational excellence to maintain SLAs for production agents
• Ensure we deploy long-term scalable agents and system integrations — not short-lived prototypes — through rigorous testing, observability, and production-readiness standards

A day in the life
This role partners with data and systems organizations across OTS to drive automations, solution development, and agentic AI tools that provide a prescriptive mindset for our field operations, IT, and maintenance partners. You'll work with data streaming solutions, APIs, and data teams to build production-grade systems backed by AI and system integration processes.

On any given day, you might be architecting a new agent orchestration flow with a Data Scientist, debugging a ServiceNow API integration with field engineers in Luxembourg, reviewing a teammate's PR/CRs to ensure production-readiness standards, or presenting a technical design to leadership. You'll learn business processes directly from the field, understanding how technicians and engineers operate in facilities — and translate those workflows into intelligent automation. This team supports worldwide solutions that cover all Amazon sites globally and geographically, so you'll collaborate across time zones with engineers in UK, France, Luxembourg, and the US.

About the team
The Decision Intelligence team is part of the OTS Data ANCHOR organization, Amazon's data, analytics, and intelligent automation engine for global IT operations. We build and deploy AI-powered agents that automate operational workflows across Amazon's worldwide IT support, field operations, and reliability maintenance teams.

Our current portfolio includes agents for automated MCM creation, printer recommendation, severity triaging, service desk automation, and more — delivering thousands of hours in annual labor globally. We're a small, fast-moving global team of engineers, data scientists, and solutions architects spanning the US and Europe with a startup-within-Amazon mentality. We ship fast, experiment boldly, and measure everything, but we deploy with a high bar for production readiness.

You'll partner daily with Data Scientists building ML models, Data Engineers managing pipelines, Product Managers defining roadmaps, and cross-functional teams across OTS and RME. Our work directly supports the technicians and engineers who keep Amazon's facilities running for customers worldwide.

Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.