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 — whichever suits you).

• Compensation is competitive; we’ll discuss it openly on the first call.

Interested? Drop your resume and we’ll set up a call. If it isn’t the right fit we’ll tell you quickly — and tell you why.