AI Product Lead (Principal Product Manager)
New
J
JobgetherAI insurance marketplace
Remote work arrangement within the United States.Full-TimeLead
SalaryAnnual base salary of $174,800–$205,700 USD
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Job Details
- Experience
- At least 8 years of experience in product management, engineering, or a closely related field at a technology company, including senior ownership of a product area.
- Required Skills
- PythonSQLProduct ManagementLLM
Requirements
- Have at least 8 years of experience in product management, engineering, or a closely related field at a technology company, including senior ownership of a product area.
- Demonstrate experience building and shipping AI-powered products or agent-based systems into production.
- Understand AI evaluation methods, including measurable tests, failure modes, and criteria for rolling back a product or model.
- Have working knowledge of agent architectures, large language models, retrieval, orchestration, guardrails, and cost, latency, and performance trade-offs.
- Have sufficient technical depth to participate in architecture and code reviews and collaborate with engineers.
- Be proficient in SQL for independent data analysis and comfortable using Python for lightweight prototyping.
- Have experience leading complex projects with small teams and delivering measurable outcomes.
- Have experience defining requirements for complex technical systems or platforms.
- Use data-driven decision-making, strategic thinking, and disciplined execution.
- Communicate technical concepts and product decisions to technical and non-technical stakeholders.
Responsibilities
- Define and own the product roadmap, balancing AI agent needs, technical architecture, and business objectives.
- Own the agent-facing product experience, including data exchange, recommendations, reasoning, integrations, and trust signals.
- Develop evaluation datasets, identify potential failure modes, and define measurable standards for successful agent interactions.
- Monitor agent performance using task completion, accuracy, response speed, and successful follow-through after handoffs.
- Build and test rapid prototypes of agent workflows with real or simulated agents.
- Translate agent behavior and experimentation insights into improvements to data models, exposed reasoning, product functionality, and system architecture.
- Partner with AI technical leadership and engineering teams to evaluate architectural trade-offs and optimize cost and performance.
- Develop relationships with AI platforms to understand how their agents discover, select, and interact with external services.
- Define requirements for complex technical systems and keep product execution aligned with the overall vision.
- Provide leadership with updates on progress, insights, risks, and strategic decisions.
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