Agentic Software Engineer

Hireology•Chicago, IL

22h•Hybrid

About The Position

Hireology's Business Technology team builds the tools, workflows, and automations that the rest of the company runs on, from Finance and Revenue Operations to Sales, Customer Success, IT, and Implementation. As an Agentic Software Engineer, you’ll design, architect, and build software solutions that make the day-to-day work of those teams faster and less painful. This isn’t a role where you sit behind a ticket queue. Business Technology is a new department, and you’ll be on the ground with non-technical colleagues regularly, helping them figure out what they actually need and then building it. If you can hold a real conversation with a CFO or a CS manager and then go write the code, you’ll fit right in. Hireology moves fast and makes decisions quickly. You’ll be context switching between teams, problems, and priorities on a regular basis, and that should energize you, not drain you. If you do your best work in a stable, predictable environment, this probably isn’t the right fit. Hireology has adopted a full AI Software Development Lifecycle. Our engineers spend less time writing code by hand and more time on spec-driven development, context engineering, and working alongside AI agents. We use Claude Code, the Superpowers framework, and the BMAD methodology, and while we lean on these tools heavily, we are very opinionated about the code that comes out the other side. Quality, maintainability, and good engineering judgment still matter, and it’s your job to make sure the output meets that bar. To be clear, this is not an invitation for vibe coders. We want real software engineering talent who genuinely knows how to build, but has made the shift to what modern engineering actually looks like. In practice, this means you operate more like a manager than a solo developer. You’re directing agents, reviewing their output, correcting their course, and making judgment calls on what good looks like. The quality of what gets built depends heavily on how well you understand the problem in the first place, which means you have to lead with genuine customer empathy. You need to sit with people, understand how they actually work, and break down their problems in a way that’s clear enough for both humans and AI to act on. Strong problem decomposition is at the core of this role. Before any code gets written, you should be able to articulate what the real problem is, why it matters, and what a good solution looks like. If you’ve moved beyond using AI just for autocomplete and are thinking seriously about what engineering looks like when agents do more of the work, this is the right place.

Requirements

5–7 years of full-stack software engineering experience.
Strong proficiency in C# .NET and Next.js (React).
Hands-on experience in a cloud environment (AWS, Azure, GCP, or similar).
Experience with AI tooling in an engineering context, such as LLM integrations, agentic workflows, or AI-augmented development.
Familiarity with continuous deployment pipelines and feature flagging (e.g., LaunchDarkly).
Working knowledge of Test-Driven Development (TDD).
Comfortable evaluating third-party systems, understanding their APIs and capabilities, and building integrations and data flows between them.
Able to work independently and communicate proactively with technical and non-technical stakeholders alike.
Based in the Chicago area or willing to relocate; able to work on-site at least 3 days per week for this role.

Nice To Haves

Microsoft Azure experience is a strong plus, as it is our primary cloud platform.
Experience with agentic frameworks such as Claude Code, Superpowers, BMAD, or comparable tooling.
Background supporting internal business systems across Finance, RevOps, CS, or similar functions.
Familiarity with MCP (Model Context Protocol) servers, plugins, or skills ecosystems.
Experience with prompt engineering, context engineering, or spec-driven development practices.

Responsibilities

Work directly with internal teams across Finance, RevOps, Sales, CS, IT, and Implementation to understand their pain points and build solutions that actually fix them.
Architect and build full-stack applications in C# .NET and Next.js, deployed in the cloud.
Build and deploy AI agents, workflows, plugins, and skills to automate internal business processes.
Work within Hireology’s AI SDLC using spec-driven and context engineering practices (Claude Code, Superpowers, BMAD).
Deeply understand the capabilities of third-party systems we use across the business and build integrations and data flows that connect them in useful ways.
Know when to reach for AI and when a simple, deterministic solution is the better call.
Make technical ideas understandable to non-technical stakeholders and collaborate with them through the design process.
Practice continuous deployment, feature flagging, and test-driven development.
Keep the team in the loop by documenting decisions, sharing progress early, and communicating proactively.
Own what you build long-term. There’s no handoff to another team once something ships. You support it, maintain it, and improve it over time.
Stay current on where AI engineering is headed and bring what you learn back to the team.