Note: The job is a remote job and is open to candidates in USA. HubSync builds a platform used by leading CPA firms and is integrating AI throughout its product and software development lifecycle. The Staff or Senior Software Engineer will build internal AI agents, embed with engineering teams to drive adoption, measure productivity improvements, and establish AI-native practices across planning, coding, review, testing, deployment, and operations.
Responsibilities
- Build internal agents as products, across the whole lifecycle. Plan: agents that turn rough asks into well-specified tickets and keep specs honest. Write: the shared harness layer (skills, context, MCP servers, per-repo configuration) that makes every engineer's agent dramatically better than stock. Review: tuned AI code reviewers, codified review rules mined from our own PR history, and the measurement that lets them earn merge authority. Test: PR-triggered QA agents on ephemeral preview environments, exploratory bug hunters, generated deterministic Playwright suites. Ship and operate: CI/CD gates, deploy verification, incident triage and RCA drafting. GitHub Actions, GitHub Apps, Claude Code / Cursor and whatever tool is actually best this quarter
- Embed and convert, team by team. This is the core of the job. Sit with each squad and service, lead by example on their own backlog (pick up their tickets and ship them the AI-native way, visibly), showcase what is possible, and remove the friction that stops adoption: permissions, infra, environments, harness config, prompt and context engineering. Success is their throughput, not your demo, and it has to land as a better day-to-day for the developers, not a mandate they resent
- Own the measurement. Cycle time, review latency, escaped defects, cost per feature, and developer experience. The goal is a step-change in every team's throughput that the developers thems elves would fight to keep
- Make the standard real. Our doctrine: individual tool choice stays free, the shared layer does not. You build and maintain the harnesses and playbooks, wire the gates (no PR ships unreviewed or untested), sharpen the doctrine with what you learn in the field, and bring the taste to know when an agent is the wrong tool
Skills
- You are demonstrably, unusually productive with AI coding tools today, and you have already lived this transition somewhere: been there, done that, seen what works and what backfires
- Not "I use Copilot": you run multiple agents in parallel, you have opinions about harnesses and context management, and you can show real PRs, tools, or automations from the last month that prove it
- Strong engineering fundamentals under the leverage: CI/CD, testing strategy, GitHub platform internals, infrastructure enough to unblock yourself (AWS), and the judgment to ship a working V1 in a day and harden it in week two
- You get more satisfaction from making a team 3x faster than from being the fastest person in the room, and you have the patience and credibility to win over skeptics with working software instead of arguments
- Show, don't tell is how you already operate
- Comfortable being measured on adoption and dollars saved, not tickets closed
Company Overview