Sr. Software Engineer (AI-Native)

Sr. Software Engineer (AI-Native)

Platform & Reliability  |  Developer Experience (DevX)

Remote (Chicago preferred)  |  Full-Time

Hireology builds purpose-built hiring software for healthcare, hospitality, and retail automotive. Our platform helps businesses attract, engage, and hire the right people, faster and with more confidence. We're headquartered in Chicago and are a team of curious, practical people who care about doing good work.

You're joining the Developer Experience (DevX) team within Hireology's Platform & Reliability department. DevX is responsible for the underlying fabric that a 40-plus person engineering organization builds on every day. When the team gets something right, every engineer at Hireology ships faster, with more confidence, and with less friction. The compounding effect of that work on the company's ability to bring high-quality product to market is significant. That's the kind of leverage this role carries.

The team's mandate spans two distinct surfaces: the internal development environment every Hireology engineer works inside every day, and the external developer experience that customers, partners, and integrators use to build on top of Hireology. Both surfaces are strategic priorities, and there is real, meaningful work to do on each one.

On the internal side, DevX owns the full development loop: CI/CD pipelines, test infrastructure, feature management, container environments, and the tooling that makes it possible for engineers to ship to production 10 or more times per day with confidence. On the external side, DevX owns the Hireology Developer Portal, the API experience, MCP server integrations, CLI tooling, and the AI skills, plugins, and agents that extend what Hireology's platform can do for developers building on it.

This role requires someone who thinks in systems, cuts through technology complexity without simplifying what shouldn't be simplified, and brings genuine obsession to the problems of developer productivity. You are not a generalist who dabbles. You go deep, you move fast, and you operate with an AI-native mindset that treats agentic tools as a first-class part of how software gets built.

Hireology has adopted a full AI Software Development Lifecycle. Engineers use Claude Code, the Superpowers framework, and the BMAD methodology to work through spec-driven development and context engineering. We lean on these tools heavily, but we are disciplined about the output. Quality, security, and maintainability are not optional. On DevX specifically, you're not just a practitioner of the AI SDLC: you're one of the people responsible for making it work well for everyone else on the engineering team.

That means building the pipelines that can handle AI-generated code at volume, designing test strategies for a world where humans write less and agents write more, and ensuring the toolchain doesn't become the bottleneck when deployment frequency is the target. Every improvement here has a multiplier effect across the entire engineering organization. Strong software discipline is non-negotiable. Agentic tools raise the ceiling on output; they don't lower the bar on what ships.

This role spans two interconnected surfaces:

Internal Developer Experience

• CI/CD & Deployment Velocity: Own pipeline performance end to end with a target of 10 or more production deployments per day. Diagnose and eliminate bottlenecks. Instrument pipelines to produce actionable data on build time, deployment frequency, change failure rate, and mean time to recovery (DORA metrics plus DX Core 4).

• AI-Native Testing Strategy: Design a testing approach that works alongside AI-generated code at volume. This includes test automation, testing in production via feature flags and canary releases, observability-driven quality validation, and progressive rollout patterns that make high-frequency, low-risk deployment possible.

• Feature Management Platform: Own the feature flagging and progressive delivery infrastructure that enables controlled rollouts, A/B testing, and rapid rollback. Ensure it's accessible and well-integrated across the engineering team.

• Container & Local Dev Optimization: Optimize the macOS development environment, including container runtime performance (evaluating and migrating from Docker Desktop where justified), dev container standards, Apple Silicon compatibility, and local iteration speed. Fast local builds translate directly into engineer productivity.

• Developer Tooling & Automation: Build internal tooling, scripts, and automations that eliminate repetitive friction across the engineering lifecycle, from local setup through production deployment. Streamline the day-to-day for every engineer on the team.

• Security-Embedded Pipelines: Embed security gates without slowing developers: secrets scanning before commits, SAST in pull request workflows, dependency vulnerability scanning, and SBOM generation for supply chain visibility. Security is built in, not bolted on.

• Azure Cloud Infrastructure: Deploy and manage Azure infrastructure as code as the team's needs evolve. Build environments that are consistent, reproducible, and cost-efficient.

External Developer Experience

• Hireology Developer Portal: Build and maintain a developer portal that gives external developers everything they need to build on Hireology: documentation, sandbox environments, authentication guides, and integration patterns. The portal is a product. Treat it like one.

• API Experience: Own the developer-facing quality of Hireology's API surface. This includes API design patterns that prioritize developer ease of use, keeping documentation in sync with actual behavior, SDK tooling, and interactive references. 80% of technical teams rate API documentation as critical to adoption. Ours should reflect that.

• MCP Server Development: Build and maintain MCP (Model Context Protocol) server integrations that expose Hireology's platform capabilities to AI agents and tooling ecosystems. As MCP becomes the standard integration layer for AI-native development, Hireology's presence in that ecosystem is a developer acquisition channel.

• CLI Tooling: Build and maintain CLI tools that give developers fast, scriptable access to Hireology's platform for automation, integration testing, and local development workflows.

• AI Skills, Plugins & Agents: Build the AI-native extensions that let developers compose Hireology capabilities into their own agentic workflows: skills, plugins, and agents that extend the platform's reach into the AI toolchain ecosystem.

• Own build and deployment pipeline performance with a concrete target: 10 or more production deployments per day, measured and improving.

• Design the AI-native test strategy for a codebase where AI agents contribute significant code volume. Move testing from a gate to an intelligence layer.

• Build and operate the Hireology Developer Portal as a product, including documentation, sandbox environments, and integration tooling for external developers.

• Develop and maintain MCP servers that expose Hireology's capabilities to the AI toolchain ecosystem.

• Build CLI tools and SDKs that give developers programmatic access to Hireology's platform.

• Build AI skills, plugins, and agents that extend Hireology's platform into agentic workflows.

• Own feature flag infrastructure and progressive delivery patterns that make high-frequency, safe releases possible.

• Optimize the macOS container environment for engineering team productivity, including evaluating and adopting alternatives to Docker Desktop where they produce measurable gains.

• Embed security practices across the development pipeline: secrets scanning, SAST, dependency auditing, and SBOM generation.

• Deploy and manage Azure cloud infrastructure as the team's needs evolve, using infrastructure as code.

• Instrument the development loop across DORA metrics and developer satisfaction measures. Use data to prioritize what gets fixed next.

• Partner with engineering teams to identify where friction lives in the development loop, and build the systems that remove it.

• Work within Hireology's AI SDLC using Claude Code, Superpowers, and BMAD methodology, with strong discipline over what ships.

• Document architectural decisions and share findings broadly so the entire engineering org benefits from what DevX learns.

We hire against these competencies:

• Obsessive learning: this role spans Next.js, .NET, Go, Ruby on Rails, Azure, and whatever comes after them. You don't need to be an expert in everything, but you have to be genuinely curious across all of it and fast at getting up to speed.

• AI-native mindset: you build with Claude Code, BMAD, and Superpowers not because the job requires it but because it's how you think about software now. You enforce discipline on what comes out the other side.

• LLM fluency: you understand how large language models work well enough to make good architectural decisions about where they help and where they don't, and you can reason about prompt design, context management, and agent behavior.

• Security mindset: secrets management, dependency hygiene, and pipeline security aren't checklists. They're habits. You design systems that are secure by default.

• Pipeline depth: you have a track record of measurable improvement to CI/CD performance and can articulate specifically what you changed and what it moved.

• Developer empathy: your colleagues are your customers on the internal side, and external developers are your customers on the other. Both deserve a great experience. You care about whether they're getting one.

• Systems thinking: a change in the test strategy affects deployment confidence. A slow local build affects how often engineers context-switch. You see how the parts connect.

• Autonomous ownership: you drive multi-month investments independently, communicate proactively, and don't need hand-holding on scope or prioritization.

• 5 or more years of software engineering experience, with meaningful time in developer tooling, platform engineering, or CI/CD infrastructure.

• Hands-on proficiency across multiple languages and frameworks: Next.js (TypeScript/React), .NET (C#), Go, and comfort working in Ruby on Rails codebases.

• Demonstrable experience improving CI/CD pipeline performance, measured in build time or deployment frequency.

• Experience designing or significantly improving automated test infrastructure, including test automation strategy, coverage approaches, and integration with deployment pipelines.

• Hands-on experience with Azure cloud infrastructure and infrastructure-as-code tooling.

• Security-aware development practices: experience with secrets management, SAST tooling, dependency scanning, or equivalent.

• Proficiency with AI-native development tools, specifically Claude Code or a directly comparable agentic coding framework, with disciplined output standards.

• Working knowledge of LLMs sufficient to make informed architectural decisions about where AI fits and where it doesn't.

• Familiarity with feature flagging platforms and progressive delivery patterns.

• Comfortable working independently in a remote environment and communicating technical tradeoffs clearly to both peers and engineering leadership.

• Experience building or maintaining developer portals, API documentation platforms, or external SDK tooling.

• Hands-on experience with MCP (Model Context Protocol) server development or equivalent AI integration protocol work.

• Background building CLI tools or SDK libraries for external developer audiences.

• Familiarity with agentic frameworks including Superpowers, BMAD, or comparable methodologies.

• Experience with macOS container optimization: OrbStack, Docker Desktop alternatives, dev containers, or Apple Silicon performance tuning.

• Knowledge of DORA metrics and DX Core 4 measurement frameworks, with experience using them to drive prioritization.

• Exposure to chaos engineering, canary release patterns, or observability-driven testing in production.

• Background in DevSecOps practices including SBOM generation, pipeline-integrated SAST/DAST, or supply chain security.

• Experience with LaunchDarkly or a comparable feature management platform.

This is a remote role. Platform & Reliability engineers work distributed, and this position is no exception. We prefer candidates in or near Chicago who can come into the office periodically for collaboration, but proximity to Chicago is a preference, not a requirement. We care more about finding the right engineer than the right zip code.

Location: Remote (Chicago or nearby preferred for occasional in-office collaboration)

• Base salary: $140,000 to $160,000 (plus bonus)

• Health, Dental, and Vision coverage from day one

• 401(k) with company match

• Unlimited PTO and mental health days

• External learning budget

• Real career advancement -- we promote from within

Must be authorized to work in the United States. We are not able to provide Visa sponsorship. Agency and/or Third Party inquiries will not be accepted.

Hireology is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, national origin, age, marital status, disability status or protected veteran status, or any other category protected under the law. All employment decisions are solely based on business needs, job requirements, and individual qualifications. We support an inclusive workplace where Hireologists excel based on personal merit, qualifications, experience, ability, and job performance.