Senior Software Engineer, Developer Platform & AI Tooling

Who We Are

We started our company to help others launch and run their own businesses, at any stage. The way we help is by keeping it simple and supporting entrepreneurs one step at a time. Put simply: our mission is to enable anyone to start, run, and grow their business while avoiding the common pitfalls that derail hopeful entrepreneurs. No more having to wade through forms, taxes, or ongoing state compliance.

We are a remote company based in Austin, Texas. We have team members from Florida to Oregon and all points in-between. Take pride in your work knowing that it shapes how people all across the country reach their goal of starting, running, and growing their business.

If the idea of helping people and working with a genuinely caring, supportive team excites you, then you’ve come to the right place.

The Role

Work with the developer platform team on a portfolio of initiatives that improve developer experience and delivery speed – from design through rollout, enablement, and measurement.

Thoroughly understand how the platform's roadmap connects to the broader business; contribute feedback to that roadmap and look for opportunities to simplify product and technical design.

Build and scale AI-powered developer tooling:

Agentic coding and review workflows that use LLMs to analyze code, generate changes, and collaborate via chat.

Policy- and guardrail-aware assistants that can comment, propose code changes, and safely automate repetitive tasks.

Prompt libraries, instructions, and service manuals that make AI adoption effective and safe across teams.

Contribute to the evolution of our CI/CD platform to be faster, more observable, and easier to adopt:

Surface insights that inform team-level improvements.

Strengthen platform reliability and security in Kubernetes:

Improve cluster/app resiliency, rollout strategies, and priority classes for critical services.

Apply Helm chart patterns, deployment practices, and IaC workflows.

Contribute to incident response playbooks, maintenance modes, and recovery patterns.

Create paved paths and golden templates for developers:

Self-service software templates, CLI/automation enhancements, and bootstrap flows.

Clear docs, runbooks, and technical blogs that drive adoption and reduce support load.

Collaborate and grow:

Pair with teammates on complex changes, champion code review quality, and share practices within the team.

Ensure your commitments are realistic given priority and urgency, and deliver on them accordingly. Anticipate and communicate blockers, delays, and scope changes before they require escalation. Keep expectations clear among everyone involved.

Qualifications

• A track record of building platform capabilities with clear outcomes in developer velocity, reliability, and/or quality.
• Solid experience in one or more of the following and working knowledge of the rest: CI/CD systems and reusable pipeline components (e.g., GitHub Actions or similar).
• Kubernetes, Helm, GitOps (e.g., ArgoCD), and infrastructure as code (e.g., Terraform).
• AI for engineering: prompt design, multi-agent orchestration, safety/guardrails, and integrating LLMs into code and review workflows.
• Proficiency in at least two languages used for platform work (e.g., Python, TypeScript/Node.js, Bash); comfortable moving across stacks to ship end-to-end solutions.
• Strong security and reliability instincts (secrets, least privilege, dependency hygiene, runtime hardening).
• Communicates effectively, clearly, and concisely in written and verbal form on both technical and non-technical subjects, tailored to the audience – from docs and service manuals to guides that accelerate adoption across the team.
• Actively listens to others and ensures they are understood.
• Bonus Qualifications
• Experience building agentic developer assistants that can review code, propose changes, and safely automate routine tasks.
• CDN and edge controls for maintenance and incident response.
• Platform observability improvements (logging/metrics/traces) and performance baselining.
• gRPC service enablement and runtime configuration patterns.
• Exposure to commercial LLM providers (e.g., Anthropic) and safe rollout patterns in enterprise settings.