Senior Backend Software Engineer – Agentic AI Workflows (Go/AWS)

About the role Most backend roles touching “AI” mean a chatbot bolted onto a CRUD app. This one is different: the agentic workflows are the product surface. You’ll work on an established enterprise asset-and-metadata platform, building the AI engine that proposes metadata across the active project estate, the automated logic that reassigns or retires ownerless systems, and a live inventory of every agent and MCP server running across production and endpoint environments — all exposed through the platform API. It’s Go on AWS , against a real production codebase with real users. A large part of the job is reading code you didn’t write, understanding how it behaves, and then extending, refactoring or decommissioning it without breaking anything. What you’ll own AI-suggested metadata engine — proposing metadata across the active project estate, then tuning it until engineers actually accept the suggestions. Automated ownership reassignment and deprecation — logic that finds ownerless or relinquished systems and acts on them safely. Agent and MCP inventory — complete coverage across production and endpoint environments, accessible programmatically. First-party product inventory and critical-user-journey mapping — making ownership and metadata trustworthy enough to decide on. Legacy refactoring and decommissioning — with unit and integration tests covering everything you ship. Sprint delivery alongside program and customer teams. Requirements — check yourself against this list You should be able to say yes to essentially all of these: 5+ years professional backend software engineering Go as a working language — you’ve built and shipped scalable backend services and APIs in it PostgreSQL — schema design and real querying MongoDB — schema design and real querying AWS — working knowledge of the services plus their client libraries and APIs Agentic, AI-driven workflows you have designed, implemented and tuned — suggestion engines, automated decision logic, or assistant interfaces Asset discovery / ingestion tooling — open-source or commercial (e.g. CloudQuery) for aggregating cloud resources and metadata Data classification standards, dependency mapping, functional framework mapping Navigating a large, unfamiliar codebase to refactor or decommission legacy code without regressing existing behaviour Unit and integration testing for backend components, as standard practice Agile/Scrum delivery — sprints, stand-ups, retrospectives Bachelor’s in Computer Science or a related field, or equivalent practical experience — we care about what you’ve built Nice to have — not required IT asset management, CMDB , or configuration management platforms Model Context Protocol (MCP) and related agent tooling patterns Governance, risk or compliance workflows — findings management, risk remediation Logistics Remote, United States. No relocation. Contract engagement , starting mid-September 2026 (W2 or 1099 —…