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

Role description

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.