Software Engineering Manager Jobs in the United States

The Role

ZenBusiness is hiring a Sr. Engineering Manager to lead a team of engineers and the AI agents they work with, to ship products that help small business owners start, run, and grow their businesses. Part of the job is finding where AI makes those products more useful and valuable for customers. You will partner with product, design, and marketing to decide what to build, then own delivery from idea to production to ongoing maintenance. We move fast, ship often, and hold a high bar. This is a hands-on role. You stay close enough to the code to make good design calls, unblock your team, and earn their trust.

This position will report to the Vice President of Engineering, and this is a remote role.

How We Work With AI

AI is central to how we build at ZenBusiness. Our engineers use Claude, Cursor, Codex/ChatGPT, and Gemini every day. Every engineer has access to these tools, plus shared skills, MCP servers, and team context that help agents work well in our codebase. We run AI pull request reviews and automated risk assessments, use agents to handle production triage, and are building a shared harness to orchestrate agent-driven delivery. We expect you to push this further.

• You use AI tools and coding agents in your own work every day: writing and reviewing code, drafting specs, and analyzing data
• You run your management work with agents too: standup synthesis, 1:1 prep, planning, goal tracking, and performance reviews
• You set the standard for how your team works with agents, and you raise the team's AI fluency through coaching, pairing, and shared practices
• You find repetitive or error-prone work in your team's delivery process (testing, triage, releases, documentation) and hand it to agents and automation, with guardrails that keep quality high
• You track your team's AI adoption, impact, and spend, and make sure the tooling pays for itself

Responsibilities

• Own outcomes, not output. You answer for whether your team's work moves the business metrics it's tied to, not just velocity or team health
• Run your area like an owner. Set the roadmap with your PM, say no to work that won't move the numbers, and step into the product role when there's no PM in the room
• Build a high-agency team. Hire engineers who raise the bar, give direct and frequent feedback, act quickly on performance issues, and keep a remote team connected and accountable
• Grow the next layer of leaders. Develop senior engineers and junior managers into people who can run larger scope without you
• Lead from the front technically. Review designs and code, ship code when it unblocks the team, and run incident reviews that fix root causes
• Raise quality and speed together. Ship tested, observable code that releases safely and predictably, with agents and automation carrying more of the load
• Decide with data. Run experiments in LaunchDarkly, measure AI features with evals and customer feedback, read the results honestly, and stop work that isn't paying off
• Shape engineering beyond your team. Build reusable patterns for working with agents that other teams adopt, and contribute to architecture, platform, and AI practices across ZenBusiness

Qualifications

• 3+ years leading and growing high-performing engineering teams that ship web-based products, including experience managing other managers
• 8+ years of software engineering experience, with recent hands-on time in a modern web stack
• Daily, hands-on fluency with agentic engineering workflows and tools such as Claude Code, Cursor, or Codex, and a clear point of view on how they change the way teams build software
• Proof you've used AI and automation to measurably improve a team's delivery speed or quality
• A record of tying your team's work to business results, with the metrics to show it
• A record of building teams people want to work on again, including engineers you've grown into leaders
• Clear, concise writing. You can make a decision, explain it on one page, and defend it

Bonus Qualifications

• Experience shipping LLM-powered products, agents, or evaluation frameworks
• Experience building internal tooling that helps engineers and agents work together
• Experience at a high-growth startup or on a lean, small-team setup
• Fintech, compliance, or small business domain experience
• Experience building shared AI context for a team: skills, MCP servers, and agent instructions
• Experience evaluating and rolling out new AI tools as they emerge