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

Ontrac Solutions Llc; Chicago (IL); Remote; USD 150,000 - 190,000; Full time

Job summary

Ontrac Solutions Llc in the United States is seeking a senior backend engineer to build the AI-enabled engine that proposes metadata across the active project estate. You’ll work on a Go-based production codebase on AWS, reading unfamiliar code, refactoring, and extending it without breaking existing behavior.

You’ll own AI-driven metadata, automated ownership reassignment, and an inventory of agent and MCP endpoints, with unit and integration tests and Agile delivery alongside cross-functional

Qualifications

• 5+ years professional backend software engineering.
• Go as a working language with scalable backend services and APIs.
• PostgreSQL: schema design and querying.
• MongoDB: schema design and querying.
• AWS: services, client libraries and APIs.
• Agentic AI-driven workflows you have designed, implemented and tuned.
• Asset discovery/ingestion tooling experience.
• Data classification standards, dependency mapping, functional framework mapping.
• Navigate large, unfamiliar codebases to refactor without regressing behaviour.
• Unit and integration testing as standard practice.
• Agile/Scrum delivery practices.

Responsibilities

• AI-suggested metadata engine development and tuning.
• Automated ownership reassignment and deprecation logic.
• Agent and MCP inventory across production and endpoint environments.
• First-party product inventory and critical-user-journey mapping.
• Legacy refactoring and decommissioning with tests.
• Sprint delivery alongside program and customer teams.

Skills

Go

Backend engineering

PostgreSQL

MongoDB

AWS

AI-driven workflows

Asset discovery

Data classification

Codebase navigation

Unit and integration testing

Agile/Scrum

CS degree or equivalent

Education

Bachelor’s in Computer Science or related field

Equivalent practical experience

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:

1. 5+ years professional backend software engineering
2. Go as a working language — you’ve built and shipped scalable backend services and APIs in it
3. PostgreSQL — schema design and real querying
4. MongoDB — schema design and real querying
5. AWS — working knowledge of the services plus their client libraries and APIs
6. Agentic, AI-driven workflows you have designed, implemented and tuned — suggestion engines, automated decision logic, or assistant interfaces
7. Asset discovery / ingestion tooling — open-source or commercial (e.g. CloudQuery) for aggregating cloud resources and metadata
8. Data classification standards, dependency mapping, functional framework mapping
9. Navigating a large, unfamiliar codebase to refactor or decommission legacy code without regressing existing behaviour
10. Unit and integration testing for backend components, as standard practice
11. Agile/Scrum delivery — sprints, stand-ups, retrospectives
12. 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.