Product Manager

About Metaforms

At Metaforms, we're redefining how market research gets done.

Market research still runs on legacy survey platforms, manual project operations, fragmented handoffs, and domain expertise locked in a few specialists' heads. Metaforms is building the agent layer that makes this work dramatically more efficient — without lowering the bar for quality, accuracy, or client trust.

Our vertically integrated AI platform empowers agencies like Dynata, Savanta, and Borderless Access to scale 10x faster, with AI Agents augmenting survey programming, data processing, and project management. We process 1,000+ surveys monthly, serve agencies working with Fortune 500 companies, and are backed by $9M in Series A funding to aggressively scale.

The product surface here is unusual. Surveys behave like programs, business workflows contain hidden operational nuance, and a small mistake creates real downstream cost for an agency and its clients. Product thinking at Metaforms isn't about copying familiar SaaS patterns — it's about understanding how work actually gets done, identifying where AI agents can reliably help, and shaping systems that feel intuitive to users while introducing genuinely new workflows underneath.

The Role

We're hiring a Product Manager to define and ship new AI-native products and workflow experiences for research operations. The role sits at the intersection of user discovery, domain synthesis, product design, and engineering execution.

You'll go end to end — from interviewing users and subject matter experts, to identifying operational bottlenecks, to translating business needs into concrete requirements, to partnering closely with engineering through delivery.

This is a high-ownership role for someone who thrives in ambiguous spaces, reasons from first principles, and builds from zero rather than relying on existing category templates.

What You'll Own

User Discovery & Problem Definition

Conduct frequent interviews with research operators, project managers, survey programmers, and agency leaders to understand how work actually happens

Turn messy qualitative input into clear product insights, problem statements, and opportunity areas

Work closely with subject matter experts to separate surface requests from deeper workflow and systems problems

Build conviction on where AI agents can remove manual effort, improve turnaround, or raise quality — without disrupting critical trust points

Product Design & 0→1 Development

Define new product concepts, workflow patterns, and operating models for AI-assisted research work

Design familiar-feeling user journeys that introduce new capabilities without overwhelming users

Write requirements specific enough for engineering to execute, while preserving room for iteration where the solution space is still emerging

Iterate rapidly on prototypes, internal feedback, and early customer usage to converge on products that are both useful and operationally viable

Cross-Functional Execution

Translate business requirements into clear engineering asks — scope, constraints, acceptance criteria, and edge cases

Partner tightly with engineering, design, operations, and domain experts through the build cycle

Drive prioritization by balancing customer value, technical feasibility, reliability risk, and speed

Ensure the team is solving the right problem, not just shipping the fastest version of the first idea

Product Quality & Adoption

Define what "good" looks like for product outcomes, user trust, and workflow adoption

Identify failure modes in user flows, handoffs, and agent behavior — especially in high-consequence operational steps

Close the loop between shipped behavior, customer feedback, and roadmap decisions

Own rollout, onboarding, and change management with customer success and operators so new workflows land in real agency production — including how adoption and efficiency gains are measured

Representative Problems You Might Work On

Designing an AI-assisted workflow that turns a raw client questionnaire into an executable survey build process

Creating review and approval loops where human operators guide or validate agent output without adding unnecessary friction

Reworking a fragmented project-management flow into a single experience that makes bottlenecks, state, and exceptions visible

Defining how internal subject matter experts collaborate with product and engineering to encode operational knowledge into a scalable system

Building product surfaces that feel familiar to agency teams while delivering step-change improvements in speed and efficiency

What We're Looking For

Must-have

Proven product management experience shipping software from concept to launch

Demonstrated ability to operate in ambiguous, early-stage, or zero-to-one environments

Strong user discovery skills — interviewing, pattern extraction, and synthesis into product direction

Comfort going deep with subject matter experts and operational stakeholders in initially unfamiliar domains

Ability to write requirements engineering can execute without a translator — including constraints, edge cases, and failure modes

Strong product judgment across scope, workflow design, trade-offs, and iterative delivery

Willingness to reason about AI/agent behavior in production: when to trust automation, when to require human review, and how quality and reliability show up for users

Bias toward defining and tracking workflow outcomes (speed, quality, trust, adoption) — not just shipped scope

Excellent written and verbal communication; direct, high-ownership style under incomplete information — clarity over polish, and willingness to call out when direction is wrong

Nice-to-have

Experience building AI-native, automation-first, or workflow software — especially human-in-the-loop or reliability-sensitive systems

Experience partnering closely with engineering on technically complex platforms

Experience on products used by operations teams, services teams, or expert users

Exposure to market research, survey tooling, data operations, or adjacent workflow-heavy B2B domains (high-leverage, not required)

How Success Looks

Users say the product fits how their work actually happens — not how software teams assumed it happened

Engineering gets clear, high-signal product inputs and moves fast without repeated ambiguity tax

New workflows feel intuitive enough to adopt, while delivering meaningful gains in speed, quality, or operational leverage

Shipped workflows show measurable gains in turnaround, quality, or adoption, with failure modes understood and managed — not just features launched

Why Metaforms

Work on AI products operating in real production environments — not demos or feature theater

Shape entirely new workflow categories instead of incrementally copying existing tools

Join a team where product, engineering, and domain understanding are tightly coupled

Operate with high ownership, fast iteration loops, zero bureaucracy, and direct influence on what gets built

Benefits

Full family health insurance

$1,000 USD annual reimbursement for skill development

Dedicated mentor/coach support

Free lunch and dinner at the office

Monthly food and snacks allowance