Who We Are:

17A is a new type of management consulting firm. We come from places like McKinsey, Palantir, JP Morgan Philanthropies, and venture-backed Healthcare startups. We share a common goal: improving the quality of government and social services. 17A believes that trust in government is something to be continuously built and earned, through strong service delivery.

We have a dynamic core team, and partner with Consultants, known internally as Project-Based Team Members, to bring the best combination of expertise to what we do. Our team has varied skills from a range of industries and experiences, including management consulting, technology and analytics, and public service. If you've spent the early part of your career in consulting or a fast-paced analytical environment and you're ready to apply those skills to something with direct civic impact, 17A is for you.

The Opportunity:

We’re looking for an experienced, technically fluent Technical Product Manager to join our team and own the products we build with our clients — from the first fuzzy problem statement to the tool a caseworker, organizer, or program officer is still using six months later. This role sits at the intersection of product management, applied AI, and public-sector delivery. This isn’t a role where you write requirements and hand them off to someone else — and it isn’t a traditional software PM seat with a proprietary roadmap to defend. You’ll sit with agencies, nonprofits, and cross-sector coalitions to decide what’s worth building, what “good” looks like, and whether it’s actually working.

This is a services model, not a product company. Every engagement is shaped around one client’s real constraints, and the client’s outcome — not feature count or launch dates — is the measure of success. We’re looking for someone who gets energized by a sharper question: when we build AI and data tools for the people who serve the public, how do we make sure what we ship is trusted, gets used, and changes how the work gets done?

What You’ll Do:

Define the product, before there’s a spec

• Run discovery with client leadership and, just as importantly, with the frontline users — caseworkers, organizers, outreach teams, program staff — to understand the real workflow the tool has to fit
• Turn an ambiguous programmatic goal (“help us reach the families with the most to gain”) into a clear product vision, a prioritized roadmap, and success metrics the client agrees to up front
• Surface and write down the assumptions and constraints that will shape what’s possible — data availability and quality, privacy and legal limits, staffing, procurement — and re-scope openly when the data or the field tells you something new

Own the backlog and the build

• Act as product owner for the engagement’s build team: write clear user stories and acceptance criteria, prioritize the backlog, run planning and review, and make the trade-off calls that keep the team moving
• Work daily with our Applied AI Leads, engineers, and data staff — read an API spec, reason about a data pipeline or model design, and push back on a technical approach when it doesn’t serve the user
• Prototype to learn: mock up, wireframe, or stand up a rough working version so clients and end users react to something real instead of a requirements document
• Own release and rollout: user acceptance testing with the client, training and onboarding for end users, documentation, and clean hand-off
• Know the buy-vs-build-vs-integrate line — when to stand up a custom tool versus recommend an existing product — and be able to defend that call to a client

Get AI right where it matters

• Decide where AI-driven output can be trusted to act and where a human should review it — eligibility, prioritization, and outreach decisions that affect real people deserve deliberate design
• Define how quality is measured for each part of the product — what accuracy means, how it’s tested before launch and monitored after, how the system fails safely, and how errors get surfaced and fixed
• Work with the client and our team to build privacy, data-sharing, security, accessibility, and equity requirements into the product from the start, not as a late-stage review

Measurement and iteration

• Build the feedback loop that shows whether the work is succeeding, not just whether it shipped — adoption, sustained use after the first month, time saved for end users, reach, and ultimately outcomes for the people the client is trying to serve
• Use that evidence each cycle to decide what to fix, cut, or build next, and report progress and trade-offs plainly to client leadership
• Where it makes sense, spot what’s reusable across engagements — a data model, a scoring approach, a field-tool pattern, an evaluation template — and help package it so the next team starts ahead

Stakeholder management

• Serve as a primary product point of contact for client counterparts, including senior officials or coalition leadership
• Communicate cleanly across technical and non-technical audiences — the same explanation should land with an engineer and with a program director
• Build trust with partners navigating high-pressure, high-visibility work

Lead and coach

• As you grow in the role, lead the product function of a small, dedicated pod embedded with a single client, answering to that client as if it were your sole focus
• Coach more junior team members on product craft and on the client-facing translation work

The Skillset:

This role is for someone who wants to work hand-in-hand with clients and end users to understand the problem and design the path to results, and who has the technical depth to hold their own with the engineers building it. You likely:

• Have 5–7 years of experience in product management, product ownership, or a closely related role (technical PM, forward-deployed, solutions) where you owned a product end to end — discovery, launch, and the iteration after. We’re especially interested in people from forward-deployed / embedded AI companies.applied-AI startups, technical product roles at fast-moving tech companies, or consulting backgrounds with real product exposure
• Have real technical depth: you can reason about how a system fits together, read an API spec, understand a modern data stack and data pipelines, and work with engineers without needing a translator — and you’re comfortable with SQL or light scripting to answer your own questions
• Understand how LLM-based and agentic products are built and evaluated — prompts, retrieval, evals, failure modes — and have informed opinions on when to trust model output and when not to
• Are comfortable in a services model: no proprietary product to fall back on, every engagement shaped around one client’s actual constraints, and the client’s outcome as the measure of success
• Have shipped something that a non-technical end user actually used to do their job differently — and can explain how you knew it was working
• Can work directly with clients — translating a policy or programmatic goal into a product plan, and translating a technical constraint back into plain English for a non-technical stakeholder
• Are genuinely obsessed with what AI can do right now, and equally genuinely care whether it does anything for people who are usually left out of that story
• Have experience or strong interest in public sector, civic tech, or applied-AI-for-impact work (prior government/nonprofit experience is a plus, not a requirement — we’ll take a phenomenal product person who’s never touched government over a mediocre one who has)
• Can work under compressed timelines without losing rigor — comfortable making and documenting tradeoffs
• Are low ego, high ownership — you do what the work requires, including the unglamorous parts (backlog cleanup, user acceptance testing, the twentieth stakeholder call, the training session nobody thanked you for)

It’s a plus if you have:

• Built prototypes yourself, in code or with AI-assisted tools, rather than only in slides or wireframes
• Worked on social services, benefits, or public-program delivery — inside government, a nonprofit, or a vendor serving them
• Experience with case-management, CRM, or field-operations tools (canvassing, outreach, or similar)

Location:

This position is remote eligible within the United States.

Compensation and Benefits:

This is a full-time role with a competitive annual salary commensurate with experience, plus performance-based incentives, health benefits, paid time off, company holidays, and life and disability insurance.

Accommodation Statement:

Improving public service delivery requires a team with diverse backgrounds and perspectives. We are an equal opportunity employer committed to diversity and inclusion. We prohibit discrimination and harassment of any kind based race, color, creed, religion, national origin, sex, gender identity, sexual orientation, disability, age, marital status, familial status, pregnancy or pregnancy-related conditions, domestic violence victim status, prior arrest or conviction record, military status, predisposing genetic characteristics, membership or activity in a local human rights commission, or status with regard to public assistance.

We encourage and welcome applicants who identify with groups traditionally underrepresented in government to apply.

Please contact recruiting@group17a.com, if you would like to request reasonable accommodation during the application or interview process.