Sr. Manager, Software Engineering

OpenGov•Dubuque, IA

3d•$200,000 - $247,000

About The Position

OpenGov seeks an experienced Sr. Manager, Engineering to lead our Enterprise Asset Management (EAM)engineering teams. This role is ideal for a leader who thrives in a fast-paced, multi-tenant SaaS environment and is passionate about building scalable, secure, and highly reliable cloud-native solutions on AWS using .NET and Angular. Our Enterprise Asset Management team designs and delivers robust applications that streamline asset management workflows and significantly enhance the user experience for local and state governments. In this role, you will set technical direction, shape the long-term strategy of our Asset Management platform, and mentor a high-performing team of engineers. If you are energized by turning complex problems into elegant, scalable SaaS solutions—and by growing engineers into technical leaders—we’d love to have you join us. At OpenGov, our mission is to power a more effective and accountable government. We offer a collaborative, diverse, and supportive environment where your work directly impacts public-sector outcomes. With strong opportunities for professional growth, continuous learning, and flexible work arrangements, you’ll be part of a team committed to innovation and engineering excellence.

Requirements

10+ years of combined experience, including 5+ years of engineering management with direct reports across multiple teams simultaneously.
Proven expertise in AWS cloud services and cloud-native, multi-tenant SaaS architecture.
Comprehensive understanding of API design, distributed systems, microservices, and CI/CD pipelines.
5+ years of hands-on software development, with recent experience in JavaScript/TypeScript, Node.js, or React. Candidates must still be comfortable in code reviews, architecture discussions, and system design sessions, not just slide decks.
Demonstrated success building and scaling small, high-output squads (3–6 engineers) that ship with outsized impact relative to team size.
Hands-on experience shipping AI-powered products, including but not limited to LLM integrations, agentic workflows, RAG pipelines, in a production environment.
Demonstrated AI execution mindset: comfortable shipping experimental, probabilistic systems; experience iterating quickly on AI features with incomplete specs and evolving requirements.
Track record of tight delivery cycles: weekly or faster deployment cadences, end-to-end ownership from scoping through production.
Demonstrated comfort operating in ambiguous, fast-moving environments . This role requires shipping real products in conditions of incomplete information, not just managing well-defined roadmaps.
Evidence of using metrics to drive decisions: success indicators, delivery velocity, quality signals, and team health are expected inputs to your leadership, not afterthoughts.
Exceptional communicator and cross-functional collaborator, who is able to influence technical and non-technical stakeholders, partner effectively with Product, Design, Data, and go-to-market teams, and represent engineering clearly across all levels of the organization.

Nice To Haves

Experience with AI agent platforms, orchestration frameworks, or developer tooling for AI is strongly preferred.

Responsibilities

Strategic Vision: Collaborate with senior leadership to develop and execute a comprehensive technical strategy that aligns with the company's long-term objectives, ensuring a robust and future-proof engineering roadmap.
Set the technical direction for how we scale with AI, not around it. That means rethinking processes, infrastructure, and team structure for a world where agents are first-class members of your engineering organization.
Influence senior leadership and stakeholders by providing insights and recommendations on technology trends, competitive landscape, and strategic opportunities.
Leadership and Management: Lead multiple engineering teams, including senior and mid-level engineers, providing strategic direction and ensuring cohesive execution across all projects.
Hire engineers who build with AI as instinct, not afterthought. Then create the environment where they grow fast, stay sharp, and do the best work of their careers.
Foster a collaborative environment between teams, promoting information sharing, best practices, and a unified approach to product development.
Spearhead major cross-functional initiatives, ensuring their successful execution and alignment with the company’s strategic objectives.
Technical Expertise: Own the architecture of a multi-tenant AI agent platform on AWS, setting the technical bar for how we build systems that are secure, reliable, and designed to scale as agents become first-class infrastructure.
Stay ahead of the AI curve by evaluating, adopting, and killing technologies fast enough that our stack is always a competitive advantage, never a liability.
Collaboration and Communication: Work closely with product managers, designers, and architects to ensure alignment between technical capabilities and business goals.
Maintain clear and transparent communication channels within and across teams, providing updates on project status, system architecture, and timeline expectations.
Coordinate with distributed teams to ensure seamless feature delivery in a fast-paced and collaborative environment.
Operational Excellence: Define and enforce stringent Service Level Agreements (SLAs) and reliability metrics, driving operational excellence and customer satisfaction.
Building AI-native systems that reduce operational drag while shipping faster than the team thought possible.
Lead initiatives that promote a culture of continuous improvement, embedding best practices and operational efficiencies across the engineering organization.