Lead Product Manager, Agent Runtime & Evals
New
J
Juniper SquareAI platform
Location: Americas (USA or Canada); this role welcomes exceptional candidates from elsewhere in the United States and Canada.Full-TimeLead
SalaryThe U.S. salary range for this role is $200,000 - $230,000+ USD. Compensation for this position includes a base salary, equity, and a variety of benefits.
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Job Details
- Experience
- 7+ years of product management experience in B2B or Enterprise SaaS, including 3+ years operating in an AI-oriented role.
- Required Skills
- Product ManagementRegression testing
Requirements
- Have 7+ years of product management experience in B2B or Enterprise SaaS, including 3+ years in an AI-oriented role.
- Have owned a complex product area end-to-end, from strategy and roadmap through execution and iteration; zero-to-one experience is preferred.
- Understand agent evaluation, including golden datasets, data labeling, automated judges, regression testing, and when human review is needed.
- Have experience building agents and replacing human-driven processes with product and automation, supported by production evaluation and monitoring.
- Be able to partner deeply with engineers on typed contracts, structured and deterministic outputs, and agent memory.
- Understand the needs of non-engineering builders and operators overseeing large numbers of automated agents.
- Be fluent with LLMs and common AI tools such as Claude and Cursor, and able to run prototypes.
- Have strong written and verbal communication skills for explaining product decisions to engineers, designers, executives, and customers.
- Have a track record of leading through influence and setting strategy for multiple teams; mentoring or managing product managers is preferred.
- Experience with managed agent platforms such as Claude Managed Agents or Workato Genies is a bonus.
Responsibilities
- Own the vision, strategy, and roadmap for Foundry’s agent runtime, covering the lifecycle from drafting and testing through deployment, monitoring, improvement, and retirement.
- Define evaluations and model governance, including golden datasets, regression gates, and when human review is required.
- Partner with engineering on quality checks for agents that evaluate other agents.
- Define how agents retain memory and improve from experience.
- Own model routing, cost attribution, and pricing for the model-agnostic platform.
- Define connectors, credentials, access grants, agent identity, and run modes for integrations.
- Design dashboards, run history, traces, metrics, logs, kill switches, and auditability for agent oversight.
- Partner with the workflow orchestration PM on the agent registry, typed contracts, and workflow bindings.
- Partner with design and engineering to build tools for business SMEs to configure, test, and tune automations.
- Track managed agent runtimes, agent frameworks, and automation platforms, and make build, buy, and partner recommendations.
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