Product Manager - OEM

IFS•San Francisco, CA

42d•Hybrid

About The Position

We’re building intelligent, autonomous AI agents that can reason, plan, and act across real-world workflows. These agents go beyond chat — they take meaningful action, work across tools and systems, and operate in complex, high-stakes environments. As our Product Manager for OEM Engineering, you’ll lead the definition and delivery of early use cases for agentic AI. You’ll turn cutting-edge agent capabilities — like long-term memory, tool use, and planning — into applied, valuable products. You’ll be use-case–driven, but platform-aware — working closely with engineering and research to ensure what we build is feasible, scalable, and aligned with the underlying agent architecture.

Requirements

5+ years of product management or startup experience building technically complex, user-facing systems
Strong intuition for applied use cases — especially in automation, operations, or real-world workflows
Familiarity with agentic AI patterns and tooling (e.g., LLM agents, tool use, LangChain, OpenAI functions, memory systems)
Experience working closely with engineers and researchers on system-level product decisions
Strong communication, prioritization, and execution skills

Nice To Haves

Exposure to or interest in domains like logistics, field ops, manufacturing, or systems integration
Background in AI/ML infrastructure, developer platforms, robotics, or IIoT
Experience designing for human-in-the-loop or semi-autonomous systems
Hands-on experience with prototyping workflows or agents using modern frameworks (e.g. LangGraph, AutoGen)

Responsibilities

Use Case Discovery & Validation
Identify and prioritize agent use cases with high ROI: operational automation, coordination agents, internal task delegation, etc.
Work with users and stakeholders to understand their workflows, challenges, and trust boundaries.
Prototype and iterate agent behaviors in production-like environments to validate fit and reliability.
Product Design & Execution
Define the agent experience — from delegation to monitoring to escalation — for real-world scenarios.
Translate use cases into clear product specs: user flows, system interactions, prompts, safety requirements, and interfaces.
Own the roadmap and ship iteratively: starting small, learning fast, scaling wisely.
Drive OEM partnerships and product strategy to integrate and scale AI agents within enterprise software ecosystems.
Cross-Functional Collaboration
Collaborate with engineering to align product needs with agent platform capabilities (planning, memory, tool orchestration, retries, etc.).
Partner with AI research to bring experimental features into real-world settings.
Ensure the platform supports the complexity of applied, multi-step, tool-using agents.
Strategy & Metrics
Define success metrics around outcomes — time saved, accuracy improved, failures recovered — not just clicks or sessions.
Build product foundations that allow for vertical reuse, system generalization, and long-term scalability.