• Own the AI-native signal-to-action layer for Sales : design, build, and continuously improve the agents and automations that turn account/contact/product signal into qualified SDR sequences, AE opportunity actions, and CSM account and renewal actions, with clear human review and approval points before anything reaches a prospect or customer.
• Build for AE and CSM workflows specifically, not just top-of-funnel outbound : deal-risk and next-best-action surfacing for AEs managing opportunities through the pipeline, and account-health, renewal-risk, and expansion-signal surfacing for CSMs managing customers through renewal — this role's scope is the revenue organization, not one segment of it.
• Serve as product owner for systems built entirely in house : drive the roadmap, prioritization, and quality bar for the call- and deal-intelligence and other revenue systems the Applied AI team builds, in partnership with sales leadership and the RevOps/analytics counterpart.
• Design the human oversight for every agent you ship : approval gates, escalation paths, and clear ownership boundaries so SDRs, AEs, and CSMs stay in control of what goes out under their name — an agent recommends and drafts, a human approves and sends.
• Build and run evaluation frameworks for agent behavior : seed scenarios, scoring rubrics, and regression checks that prove an agent is producing good contacts, good sequencing, good deal guidance, and good call and deal intelligence output before and after it goes into production — not just that it runs.
• Instrument and monitor production agent activity : track model and tool calls, tie agent actions back to pipeline and revenue outcomes, and give sales leadership and RevOps a clear read on what the agents are actually doing and whether it's working.
• Map and redesign seller workflows with an AI-native lens : go deep with SDRs, AEs, CSMs, and RevOps to understand current-state processes — signal sourcing, contact qualification, sequencing, account prioritization, deal support, renewal management — identify where AI creates leverage versus risk, and translate findings into prioritized action plans.
• Do the GTM engineering that connects revenue systems : build against Salesforce, Outreach, Gong/call data, and third-party signal sources (e.g., procurement and contract data), and surface shared infrastructure opportunities to prevent duplicated builds with other Applied AI efforts. This role is meant to create economies of scale, not n+1 point solutions.
• Partner with AI platform, systems, and/or data engineers when required : clearly define requirements, translate business needs into actionable technical specs, and own outcomes on the business side — build first, then delegate backend complexity (data modeling, integrations, infrastructure) to platform engineering.
• Serve as the primary AI capability advisor for Sales : help sales and RevOps leaders understand what is possible with AI today, evaluate build vs. buy tradeoffs, identify where AI should not be applied due to compliance or brand-risk constraints, and set realistic expectations on scope and timeline.
• Drive adoption and change management for tools you build : shipping is not the finish line. You own ensuring that agents and workflows are understood, trusted, and refined based on real feedback from the SDRs, AEs, and CSMs who depend on them.
• Maintain a living roadmap of AI initiatives across Sales : track ideas, in-flight projects, and delivered solutions; report on impact (e.g., pipeline contribution, conversion lift, call- and deal-intelligence adoption); and continuously reprioritize based on business need and resource availability.
• Keep your impact visible to executive leadership : visibility is a core part of this role. Report on business impact on a regular cadence (monthly, in terms the executives you support can defend — conversion, pipeline contribution, renewal outcomes), alongside weekly check-ins with Applied AI leadership.
• Communicate progress, priorities, and blockers clearly across stakeholders : written updates, structured check-ins with sales leadership, RevOps, and Applied AI leadership, and crisp escalation when decisions require broader alignment.

Required Experience

• Bachelor's degree in Information Systems, Computer Science, Business Analytics, Data Analytics, or a related field.
• 4–7 years of experience in technical product management, sales/revenue operations, data science, GTM strategy or operations, solutions architecture, or a closely adjacent function. Backgrounds vary: a technical PM, a data scientist, a sales ops analyst who builds, or a GTM strategist who has taught themselves to build with Claude are all strong fits. Deep software engineering backgrounds are welcome when paired with sales or revenue operations experience. We need someone who has been hands-on, on the ground, building and improving things — not advising from a distance.
• Demonstrated experience using AI tools in a professional context — not just familiarity. You have been actively using tools like Claude, Cursor, or Codex, as well as agentic orchestration systems like n8n, make.com, or Airia, to meaningfully improve how you or your team works, and you can speak concretely about what you've built or changed as a result.
• Production experience building and operating agents, including tool use, context engineering, and evaluation frameworks — you can point to something you shipped and describe how you knew it was working.
• Past experience/exposure to GTM and Sales at a SaaS company.
• Exceptional problem-solving and first-principles thinking: you can look at a messy, manual seller process, pull it apart into its components, and design a fundamentally better solution — not just automate what exists today. You approach unfamiliar domains as an asset, not a liability.
• Strong user research and discovery skills: you build trust with sellers and RevOps before designing for them, surface the root problem underneath the surface problem, and validate solutions with the people who will actually use them.
• Ability to bridge technical and business stakeholders: you can explain a complex AI workflow to a sales stakeholder, articulate data access tradeoffs to a compliance stakeholder, and translate business requirements into engineering specs — all in the same week or even day.
• Comfort working in a code-first approach to traditionally no-code enterprise sales systems (Salesforce, Outreach, Gong, or similar). Familiarity with how enterprise revenue data flows across systems is a plus.
• Strong analytical skills: comfortable with data in spreadsheets, dashboards, or basic BI tools (Tableau, Looker, or similar), and working fluency with SQL; able to extract insight from data and frame it clearly for both technical and non-technical audiences.
• Self-starter with high initiative: you see opportunities, propose solutions, and drive them forward without waiting to be told. This role will involve significant ambiguity, and the right person will find that energizing rather than paralyzing.
• Exceptional written and verbal communication: you write clearly, you do not create information silos, and you know how to tailor your message to the audience in front of you.

• Prior experience in sales/revenue operations, customer success operations, or a forward-deployed/solutions-architecture role.
• Experience with Claude Code, the Claude Agent SDK, or building MCP servers.
• Familiarity with AI governance concepts: prompt design, data access controls, audit trails, and responsible AI principles in sensitive-data environments.
• Experience building or deploying workflow automations or internal tools without engineering support.
• Familiarity with Snowflake, Looker, or similar data platforms at a data analysis level (not data engineering).
• Applied ML and experimentation background: A/B testing, propensity models, recommendations, or lead/account scoring.
• Experience working in a fast-moving, high-growth SaaS environment where the org is actively evolving and priorities shift quickly.
• Experience working at the intersection of Sales and Marketing, or Sales and RevOps — roles that required navigating cross-functional data ownership and system permissions.
• Prior exposure to public sector or B2G sales, or other environments with elevated data handling standards.

Compensation

Chicago, IL: $150,000 - $165,000

On target ranges above include base plus a portion of variable compensation that is earned based on company and individual performance.

The final compensation will be determined by a number of factors such as qualifications, expertise, and the candidate’s geographical location.

Why OpenGov?

A Mission That Matters.

At OpenGov, public service is personal. We are passionate about our mission to power more effective and accountable government. Government that operates efficiently, adapts to change, and strengthens public trust. Some people say this is boring. We think it’s the core of our democracy.

Opportunity to Innovate

The next great wave of innovation is unfolding with AI, and it will impact everything—from the way we work to the way governments interact with their residents. Join a trusted team with the passion, technology, and expertise to drive innovation and bring AI to local government. We’ve touched 2,000 communities so far, and we’re just getting started.

A Team of Passionate, Driven People

This isn’t your typical 9-to-5 job; we operate in a fast-paced, results-driven environment where impact matters more than simply clocking in and out. Our global team of 800+ employees is united in our commitment to challenge the status quo. OpenGov is headquartered in San Francisco and has offices in Atlanta, Boston, Chicago, Dubuque, Dallas, and Pune.

A Place to Make Your Mark

We pride ourselves on our performance-based culture, where every employee is encouraged to jump in head-first and take action to help us improve. If you have a great idea, we want to hear it. Excellent performance is recognized and rewarded, and we love to promote from within.

• Comprehensive healthcare options for individuals and families
• Flexible vacation policy and paid company holidays
• 401(k) with company match
• Paid parental leave, wellness stipends, and HSA contributions
• Professional development and growth opportunities
• A collaborative office environment with weekly catered lunches.