SysDev Eng, OTS - Data ANCHOR Team

Description

Are you a builder who gets energized turning ideas into production systems? Do you want to build AI-powered agents and data-driven solutions that solve real-world operational problems at Amazon's global scale? If working with GenAI, data infrastructure, streaming APIs, and shipping solutions fast excites you — this role is for you.

Amazon's Ops Tech Solutions (OTS) Data ANCHOR organization is seeking a Systems Development Engineer with a software development background and passion for AI/data systems to join our Decision Intelligence team. You will build and ship agentic AI solutions and AI-enabled data infrastructure that integrates with third-party platforms (Service Now, APM etc.), first-party Amazon systems, and cross-organizational services spanning OTS and Reliability Maintenance Engineering (RME).

You will take designs and POCs and turn them into production-grade agents, MCPs (Model Context Protocols), and data-driven automation systems that drive measurable impact across Amazon's worldwide operations. A critical part of this role is ensuring our AI agents are backed by robust, well-architected data pipelines — building the streaming connections, APIs, and data integrations that make agents intelligent and analytical tools prescriptive.

You'll own the development of Data MCPs and Analytical MCPs that power self-service data access and AI-ready infrastructure for our team and partners.

You’ll work alongside senior engineers, data scientists, and data engineers — learning business processes directly from the field and translating them into intelligent, data-backed automation that supports technicians and engineers globally.

• Build and maintain agentic AI solutions — implementing agent orchestration logic, API integrations with Service Now (3P), and Amazon internal systems (1P)
• Develop Data MCPs and Analytical MCPs that enable AI agents and partners to consume, query, and act on operational data effectively
• Build and maintain streaming data connections and APIs that feed AI agents with real-time, high-quality data inputs
• Partner with Data Scientists and Data Engineers to implement AI-ready data pipelines, ensure data quality, and develop agent capabilities (LLM tool-use, prompt templates, RAG patterns)
• Translate POCs into production-ready systems with high code quality — writing tests, documentation, and monitoring from day one

• Architect and build AI-enabled data infrastructure that ensures agents and analytical tools have reliable, governed, and performant access to data
• Build integrations across OTS and RME ecosystems, connecting agents to upstream/downstream data sources, streaming platforms, and enterprise services
• Ensure data readiness for AI — designing schemas, data contracts, and pipeline patterns that make data consumable by agents and ML models at scale
• Implement user-facing platform features and dashboards where AI integrations and analytical MCPs surface prescriptive recommendations to field partners
• Contribute to guardrails, evaluation mechanisms, and data quality checks for production AI systems

• Write clean, well-tested, production-quality code and participate in code reviews
• Own features end-to-end — from implementation through CI/CD deployment to production monitoring
• Participate in on-call rotations and drive operational excellence for production agents and data pipelines
• Deploy long-term scalable solutions — not throwaway prototypes — with observability, alerting, and production-readiness standards

This role partners with data and systems organizations across OTS to build automations, data solutions, 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 robust data integration processes. On any given day, you might be building a streaming data pipeline that feeds an AI agent's decision engine, developing an Analytical MCP that…