- Own the product vision, strategy, and roadmap for Fetch's internal Agentic Platform: agent runtime and orchestration, context and memory, model routing and gateways, evaluation, observability, and governance.
- Treat the platform as a product: prioritize capabilities by what agent teams actually need next, sequence the roadmap against real agent launches, and measure success by what ships on top of the platform.
- Design the platform's human-in-the-loop and multi-agent primitives — the shared building blocks teams use to define roles, handoffs, review points, escalation paths, and feedback loops between agents and the people who oversee them.
- Partner with Fetch's developer productivity and infrastructure teams so the platform shows up to builders as one coherent experience — shared capabilities and paved paths rather than one-off solutions.
- Extend what works: as capabilities prove out with one agent team, generalize them into shared primitives other teams can adopt — building on the automation muscle Fetch has already developed.
- Define success metrics tied to platform outcomes — time from agent idea to production, adoption across teams, reliability, and quality and cost per agent task — and drive experimentation to improve them.
- Look around the corner: anticipate where the agent ecosystem is heading — MCP, agent-to-agent interop, agent identity and delegated access — and position the platform so Fetch's agents can safely work with agents and surfaces we don't control.
- Own the ADLC end to end: define how a team at Fetch takes an agent from idea through evaluation, launch, and production operations — and make that path faster, safer, and more repeatable with every release.
- Build and operationalize evaluation capabilities every agent team can use — offline evals and golden datasets before launch, production quality monitoring after.
- Define the shared building blocks of the lifecycle: prompt, schema, and tool registries; a unified programmatic interface to the platform (CLI, API, MCP); and onboarding checks for new agents and tools.
- Design governance that enables rather than blocks: least-privilege agent access, guardrails, and review points that let teams ship quickly and trust what they ship.
- Drive continuous improvement loops: prompt and context engineering, model updates, and tool design informed by eval results and real user feedback.
- Establish observability and performance metrics for agent effectiveness, reliability, and cost across the portfolio.
- Serve as the embedded researcher and voice of the teams who build on the platform: engineers, product managers, data scientists, and the operations teams who depend on what they ship.
- Run structured discovery — interviews, ride-alongs, workflow shadowing — and translate it into journey maps of the agent development lifecycle, friction inventories, and prioritized platform opportunities.
- Decide where the platform should be opinionated and where it should stay out of the way — defining the defaults, escape hatches, and override mechanisms builders need to trust the platform with production workloads.
- Own adoption as a first-class product outcome: onboarding, enablement, feedback channels, and iteration until the platform is what teams reach for by default — not just tried once.
- Close the loop between builders and the roadmap, ensuring friction, escalations, and workarounds feed directly into platform improvements and evaluation sets.
- Run the program with rigor: crisp documents, roadmaps, and status communication; dependencies tracked across many teams; nothing dropped.
- Build alignment across the many stakeholders this work touches — engineering, data, security, design, and the agent teams building on the platform.
- Translate complex technical concepts into clear business value for leadership — and translate builder and operator realities back into technical requirements for engineering.
- Communicate progress, risks, and tradeoffs clearly to senior leadership.
- Operate with a high degree of autonomy in a space where the problems, tools, and org structures are all still taking shape.
- 4+ years of Product Management experience, with meaningful time spent on platform or infrastructure products, developer tools, or AI/ML-powered products.
- Experience shipping AI/LLM-powered features to real users, with working fluency in LLMs, prompt engineering, evaluation frameworks, and agentic loops.
- Demonstrated discovery and research skills — comfortable running your own user interviews, shadowing sessions, and workflow mapping, and turning them into product requirements.
- Strong systems thinking and process design capabilities, with a track record of identifying and redesigning complex workflows.
- Exceptional organizational skills: able to run multi-team programs, manage dependencies, and keep many stakeholder groups aligned simultaneously.
- Strong analytical mindset with experience defining metrics, running experiments, and driving measurable outcomes.
- Proven ability to work cross-functionally and influence stakeholders across technical and non-technical teams — especially engineering and data science.
- Excellent written and verbal communication skills, with the ability to clearly articulate complex ideas to diverse audiences.
- Comfort operating in fast-paced, ambiguous environments where problem spaces are not yet fully defined.
- Experience building internal platforms or developer-facing products where your users are other builders — including measurable adoption, enablement, and change management.
- Experience working with AI agents, multi-agent systems, or conversational AI in production environments.
- Familiarity with the emerging agent infrastructure ecosystem: agent frameworks, MCP and agent-to-agent protocols, model gateways, and agent observability tooling.
- Familiarity with AI evaluation frameworks, prompt engineering, and quality measurement for generative AI products.
- Experience designing human-in-the-loop systems where AI output is reviewed, corrected, or approved by expert operators.
- Formal or informal UX research experience: study design, contextual inquiry, usability testing, or workflow analysis.
- Background in marketplace, rewards, loyalty, or retail media businesses.
- Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth.
- 401k Match: Dollar-for-dollar match up to 4%.
- Benefits for humans and pets: We offer comprehensive medical, dental and vision plans for everyone including your pets.
- Continuing Education: Fetch provides ten thousand per year in education reimbursement.
- Employee Resource Groups: Take part in employee-led groups that are centered around fostering a diverse and inclusive workplace through events, dialogue and advocacy. The ERGs participate in our Inclusion Council with members of executive leadership.
- Paid Time Off: On top of our flexible PTO, Fetch observes 9 paid holidays, as well as our year-end week-long break.
- Robust Leave Policies: 20 weeks of paid parental leave for primary caregivers, 14 weeks for secondary caregivers, and a flexible return to work schedule.
- Calvin Care Cash: Employees who are welcoming new family members will also receive a one time $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers and much more!
- Flexible Work Environment: Collaborate with your team in one of our stunning offices, or you can work fully remotely from anywhere in the US. We’ll ensure you are equally equipped with the hardware and software you need to get your job done in the comfort of your home. (applicable for most roles)
Skills Required
- 4+ years of Product Management experience, including meaningful experience with platform or infrastructure products, developer tools, or AI/ML-powered products.
- Experience shipping AI or LLM-powered features to real users.
- Working fluency in LLMs, prompt engineering, evaluation frameworks, and agentic loops.
- Experience conducting user interviews, shadowing sessions, workflow mapping, and translating research into product requirements.
- Strong systems thinking and process design capabilities, with experience redesigning complex workflows.
- Exceptional organizational skills, including managing multi-team programs, dependencies, and stakeholders.
- Analytical experience defining metrics, running experiments, and driving measurable outcomes.
- Ability to work cross-functionally and influence technical and non-technical stakeholders, especially engineering and data science.
- Excellent written and verbal communication skills.
- Comfort operating in fast-paced, ambiguous environments.
- Experience building internal platforms or developer-facing products with measurable adoption, enablement, and change management.
- Experience working with AI agents, multi-agent systems, or conversational AI in production.
- Familiarity with agent frameworks, MCP, agent-to-agent protocols, model gateways, and agent observability tooling.
- Familiarity with AI evaluation frameworks, prompt engineering, and generative AI quality measurement.
- Experience designing human-in-the-loop systems.
- Formal or informal UX research experience, including study design, contextual inquiry, usability testing, or workflow analysis.
- Background in marketplace, rewards, loyalty, or retail media businesses.
Fetch Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fetch and has not been reviewed or approved by Fetch.
-
Healthcare Strength — Benefits information points to comprehensive medical, dental, vision, and life insurance coverage. Feedback suggests employees value the strong health offerings alongside mental-health support.
-
Leave & Time Off Breadth — Policies include flexible or unlimited PTO, paid holidays and sick days, bereavement (including pet) and natural-disaster leave. Feedback suggests time-off breadth is a standout element of the package.
-
Wellbeing & Lifestyle Benefits — Wellness programs, 1:1 coaching, Gympass, team workouts, and nutrition counseling are provided. Office and remote perks such as home-office stipends, snacks, and pet-friendly spaces further enhance lifestyle support.
Fetch Insights
What We Do
Fetch Rewards is a mobile app that connects and rewards everyday shoppers for buying the brands they love. Fetch gives users the easiest way to save on their purchases by simply scanning any grocery receipt, from any store. For our brand partners, Fetch helps them build long-term loyalty, and understand a true 360 degree view of purchase behavior.
Why Work With Us
We put people first - both in our culture, and in our product. Our culture is built on transparency, empowerment and accountability. Our product is built on putting our customers first in everything we do - from design, to privacy and security, to new features. The result is the rapid growth we all dream of being a part of. Come join the team!
Gallery









