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Software Development Manager

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: Moonshot
Full Time position
Listed on 2026-06-03
Job specializations:
  • Software Development
    AI Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Moonshot builds the power infrastructure that makes AI possible. Our electrical distribution equipment goes into the largest AI datacenter deployments in the country; our customers include the companies building the next generation of AI compute.

Moonshot Labs is our internal technology organization. We build the software, automation, and AI agents that accelerate how a manufacturing business runs, from the shop floor to leadership. As Software Development Manager, you own the software development team: the people, the delivery, and the execution of the roadmap. You are the single point of contact between Labs software and the rest of the business, and you are hands‑on enough to set the technical bar and make real architecture calls.

You keep the team on the leading edge of applied AI, both in how they build and in what they build, from AI‑assisted development to shipping practical AI agents that put time back in people's hands. This is a build‑it leadership role reporting directly to the CTO, with scope that grows as Labs grows.

Key Responsibilities
  • Team Leadership and Development: Manage, mentor, and grow the software development team. Own hiring, 1:1s, performance management, and team structure. Develop your people and keep the quality bar high as the team scales.
  • Delivery Ownership and Process: Own the team's execution, quality, and cadence. Establish and maintain sprint structure, release process, source control, and staging discipline that let a small team ship fast without breaking production. Keep the process lightweight enough that developers follow it and rigorous enough that leadership has visibility, and adapt it as the team grows.
  • Roadmap Execution and Prioritization: In partnership with the CTO, translate company priorities into a sequenced, prioritized plan. Decide what the team builds next and why, balance competing requests, and keep the team pointed at the highest‑impact work.
  • Business Interface: Be the primary point of contact between Labs software and functional leaders across Operations, Engineering, Procurement, Finance, and IT. Understand their pain points, commit to solutions, set realistic expectations, and own the "what, why, and when" conversations so the CTO does not have to broker every request.
  • AI Adoption and Agent Development: Keep the team on the leading edge of applied AI. This space moves fast, and you own evaluating new models, tools, and frameworks, deciding what is worth adopting, and getting it into the team's daily practice. Make AI‑assisted development a standard part of how the team works, and make practical AI agents and automation a core part of what Labs ships: systems that handle real workflows, take work off people's plates, and have immediate application in production.

    You raise the whole team's AI capability, not just your own.
  • Technical Standards and Hands‑On Judgment: Set technical standards and own architecture decisions, code review practices, and technology choices. Stay hands‑on enough to evaluate trade‑offs and hold the team to a high bar.
  • Adoption and Outcomes: Make sure what the team ships gets used and drives measurable results. Coordinate rollout, gather user feedback, track adoption, and feed real‑world input back into the next iteration. A tool nobody uses is a tool that did not matter.
Qualifications Experience
  • 5+ years of professional software development experience, with at least 2 years directly leading or managing a software team, not just senior individual‑contributor work
  • Track record of shipping internal tools, web applications, data or ERP integrations, or operational software that drove measurable business outcomes
  • Experience owning delivery for a team: prioritization, sprint cadence, and release management
  • Experience in a manufacturing, industrial, or operationally complex environment is strongly preferred
Skills
  • Deep, current fluency in applied AI: building and integrating AI agents and automations (LLM APIs, agent frameworks, tool and function calling, retrieval), AI‑assisted development, and a track record of staying current as the tooling evolves. You can build agents yourself and raise the whole team's AI capability
  • Demonstrated…
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