Lead Product Manager, Agent Runtime & Evals

Juniper Square

Toronto

Remote

CAD 279,000 - 321,000

Full time

17 hours ago

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Benefits offered by this job

Health, dental, vision

Life insurance

Mental wellness

Fertility support

Flexible time off

Professional development stipend

Home office setup allowance

Job summary

Juniper Square seeks a Lead Product Manager to own the agent runtime and evaluation layer of Foundry, driving AI-driven automations for fund administration. The role blends product strategy with hands-on governance of models, data, and workflows, collaborating with engineering, design, and business teams.

The ideal candidate has 7+ years in B2B SaaS product management, strong AI fluency, and a track record of delivering complex platforms that empower non-engineers to deploy automations.

Qualifications

7+ years of product management experience in B2B or Enterprise SaaS.
Proven end-to-end ownership from strategy to execution.
Experience with AI-driven products and agent platforms.
Strong collaboration with engineering, design, and sales.
Excellent written and verbal communication.

Responsibilities

Build the agent runtime vision, strategy, and roadmap for a no-code product.
Own evaluations and model governance, with data labeling and gates.
Address evaluation of evaluators and ensure quality at scale.
Define memory, learning, and self-improvement for agents.
Own model routing, cost attribution, and pricing across jobs.
Integrate hosted agents with workflows and contracts.
Deliver configuration tools for SMEs to customize automations.
Stay ahead of the market with managed agent platforms.
Provide leadership across platform and adjacent teams.

Skills

Product management

AI/ML familiarity

Strategic thinking

Cross-functional leadership

Communication skills

User empathy

Tools

Claude

Cursor

LLMs

Job description

About Juniper Square

Private markets are one of the largest, most complex, and most underserved corners of global finance. Our mission at Juniper Square is to unlock their full potential. We’re the Operations Partner trusted by 2,300+ GPs, unifying technology, data, and fund administration services into a single platform that helps GPs move faster, make better decisions, and scale with precision. With $300B+ under administration and 700,000+ LPs on platform, we’ve built the scale to match our ambition. And with JunieAI, our purpose-built AI platform, we’re reimagining how private markets operate, embedding intelligence across every workflow. Founder-led since 2014, backed by $350M+ in funding, and now 1,000+ employees strong, we’re building a company designed to shape the future of private markets for decades to come.

About Juniper Square

Our culture is built for people who want to do ambitious, meaningful work alongside exceptionally talented teammates. We think like owners, move with urgency, and take pride in solving hard problems that truly matter to our customers and the future of private markets. We believe the best ideas come from open debate, deep collaboration, and diverse perspectives, which is why we believe transparency is the default and feedback makes us stronger. If you’re energized by high standards, rapid growth, and the opportunity to help define a category at a pivotal moment, come join us!

Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.

About Your Role

We are looking for a Lead Product Manager to own the agent runtime and evaluation layer of Foundry, the platform where Juniper Square builds, deploys, and operates AI agents, apps, and code. It is built for non-engineers: a fund administration specialist or business SME should be able to describe what they need and end up with a governed, deployable automation that has its own identity, access grants, and audit trail. You will report to the Group Product Manager for Foundry and work closely with a dedicated engineering team on the details that make that promise real.

About 75% of your time goes to the agent runtime itself: versions and deployments, evaluations and testing, and what happens when a new model ships and teams want it for some automations but not others. The other 25% goes to partnering with the workflow orchestration PM on the contracts that let hosted agents plug into governed workflows and get real work done. Think of orchestration as the shape of the container, and this role as how that container gets filled with automations in a deterministic, predictable way.

The platform is early and the problems are hard. We are rebuilding how fund administration gets done to be agentic first, with humans and agents building, configuring, and deploying automations together. You will help shape the foundations, and engineering will look to you to make the call on ambiguous platform tradeoffs.

AI fluency is a baseline expectation. PMs at this level should be comfortable using the full range of modern tools (e.g. LLMs, agent orchestration frameworks, Claude) to move faster and make sharper decisions. That might mean building and deploying your own agents on the platform you own, prototyping before writing requirements, or using coding agents to submit pull requests for engineering. The expectation is sound judgment about what will get to the best outcome for the customer and the team.

This role would benefit from in-person collaboration in San Francisco, where many of our product management, design, and engineering personnel are based, although we also welcome exceptional candidates from elsewhere in the United States and Canada.

What You’ll Do

Build the agent runtime for non-engineers: Own the vision, strategy, and roadmap for a platform where business users take an agent, app, or script from idea to governed production without an engineering cycle. Define the full lifecycle: draft, test, publish, version, deploy, run, observe, improve, and retire.
Own evaluations and model governance: Define how every automation is tested before it ships. Work with engineering and our shared eval platform team on golden datasets, data labeling, and regression gates that block promotion. Decide when an automated judge is enough and when a human has to stay in the loop. Shape how evals decide which models are eligible for which agents, so a new model release becomes a product decision rather than a scramble.
Solve the "who evaluates the evaluator" problem: Agents that grade other agents need their own checks. Partner with engineering on patterns that keep quality measurable at the scale of thousands of agents, and turn them into experiences builders can understand and trust.
Shape memory, learning, and self‑improvement: Define how agents keep long‑lived memory, compact it, and improve from experience, with an eye on adoption and user‑facing impact rather than algorithms alone.
Run a model‑agnostic platform: Own model routing, cost attribution, and pricing so teams can choose the right model for each job and see what it costs.
Integrate with broader systems: Define how hosted agents reach data and take action across our product suite, our fund administration systems of record, and third‑party tools. Own the connector, credential, and access‑grant model so integrations are reusable rather than rebuilt per agent. Define agent identity and run modes, including when an agent acts with the invoking user’s access and when it acts under its own service identity.
Give people oversight at scale: Design the tools that let fund administration teams supervise large fleets of agents: dashboards, run history, observability through traces, metrics, and logs, kill switches, and auditability. Make it clear what is an exception and what is an issue.
Define how automations bind to workflows: Partner with the workflow orchestration PM on the agent registry and typed contracts that describe what an agent needs and produces, and how workflows bind to it. Protect the safety boundary that agent‑driven steps stage changes and people release them.
Deliver configuration to business SMEs: Partner with design and engineering to build the tools SMEs use to configure, test, and tune automations themselves. Hold the line on convention over configuration so every setting earns its place.
Stay ahead of the market: Track managed agent runtimes, agent frameworks, and automation platforms. Turn that view into clear build, buy, and partner calls.
Be a leader: Set direction across the platform and adjacent teams, raise the bar for product craft, and be the person engineering trusts on ambiguous platform tradeoffs.

Qualifications

7+ years of product management experience in B2B or Enterprise SaaS, including 3+ years operating in an AI‑oriented role.
Proven experience owning a complex product area end‑to‑end, from strategy and roadmap through execution and iteration, ideally in a zero‑to‑one context.
Hands‑on understanding of how agent evaluation works: golden datasets, data labeling, automated judges, regression testing, and knowing when a human has to step in.
Background building agents and replacing human‑driven processes with product and automation, with real evaluation and monitoring discipline in production.
A strong engineering partner with a product mindset. You can go deep with engineers on topics like typed contracts between agents and workflows, structured and deterministic outputs, and agent memory, and you know the right questions to ask even when you don’t have the answers. This is not a TPM role: your focus is how people actually use these tools.
User empathy for non‑engineering builders and operators, including how people oversee large numbers of automated agents.
Fluency with LLMs and common AI tools (e.g. Claude, Cursor). You should be able to run your own prototypes and use AI to get work done faster than a traditional PM workflow would allow. Bonus points for deep experience with managed agent platforms such as Claude Managed Agents or Workato Genies, including evals, tool and connector access, versions, and deployments.
Strong communication skills, written and verbal, with the ability to articulate product decisions clearly to engineers, designers, executives, and customers alike.
Track record of leading through influence, ideally mentoring or managing other product managers, and setting strategy that multiple teams execute against.

What Success Looks Like

By the end of Q1: The platform runs real fund administration workflows with real automations, such as capital calls and distributions, built and deployed on Foundry.
Following the Q1 milestone: Those workflows roll out to the entire fund administration team, fundamentally changing how they work.
Long term: An "AI factory" where AI watches how work gets done and proposes new workflows and agents, and people move from building to oversight and course correction. A new client could be up and running in a day and fully automated within the week.

Compensation

Compensation for this position includes a base salary, equity, and a variety of benefits. The U.S. salary range for this role is $200,000 - $230,000 USD. Actual base salaries will be based on candidate‑specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable.

Benefits Include