Senior Backend Software Engineer – Agentic AI Workflows (Go/AWS)
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Job 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.
Originally posted on Himalayas
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