AI Product Manager, Agents & Orchestration

Posted Yesterday
Hiring Remotely in United States
Remote
185K-260K Annually
Senior level
Artificial Intelligence • Machine Learning • Software • Conversational AI
The Role
Own the agent runtime and orchestration platform powering AI-driven go-to-market Superhumans. Define planning, tool calling, memory, guardrails, multi-agent handoffs, packaged workflows, evaluation harnesses, APIs, and enterprise configuration. Partner with GenAI and engineering teams to ship weekly, prototype solutions, write technical specifications, and measure agent performance through task success, escalation precision, hallucination, and tool-error metrics.
Summary Generated by Built In
AI Product Manager, Agents & Orchestration

This is a fully remote opportunity and can be worked from any location in the United States.

About Us

1mind is building the next generation of revenue teams.

We are creating a new category of enterprise software: Autonomous Customer Experience. Our platform deploys Superhumans, go-to-market teammates with a face, a voice, and a GTM brain that serve the buyer across the entire journey with one continuous memory. They engage, demo, onboard, and support in the moments no company could ever staff, so the handoffs disappear and growth stops leaking.

Join us as we define the category and build the platform that powers the next generation of revenue teams. When the buyer wins, the company wins. Every1 Wins.

About the role

1mind is building the AI-led GTM workforce: Superhumans that run SDR, SE, onboarding, account management and customer success work end to end, on top of a shared context graph that compounds with every customer conversation. Today each Superhuman mostly runs as a single agent on a single surface. The next product leap is orchestration: teams of agents that hand work to each other, run packaged GTM plays, and bring in humans only when the trust ladder says so.

You'll own that leap. This is the first PM seat dedicated to the agent runtime and orchestration layer. You'll work directly with the GenAI team, report to the Chief Product Officer, and decide how agents plan, call tools, share memory, hand off, and get evaluated. Then you'll turn that into a platform that other PMs, forward-deployed engineers and customers build on.

The window is short. Large platforms are consolidating the two ends of the funnel, and the live-conversation middle is still open. Expect to ship a v1 that isn't clean, then make it better every week.

What You’ll Do
  • Own the agent runtime every Superhuman runs on: planning, tool calling, memory reads and writes against the context graph, guardrails, and the Assist, Co-pilot and Autonomous trust ladder. One runtime, many roles.

  • Design multi-agent orchestration: handoffs between Superhumans across the customer journey (inbound SDR to SE Ride-Along to onboarding to CSM), shared state across a deal or account, and conflict resolution when two agents want to act on the same contact.

  • Turn GTM orchestrations into a product. Packaged plays by funnel-stage outcome, like qualification and activation or retention and expansion, that customers configure instead of build. You define the primitives: triggers, steps, agent assignments and human checkpoints.

  • Build and own the eval harness for agent behavior, including task-level success, objection-to-advance rate, escalation precision, and hallucination and tool-error rates. Set the bar that gates every release and own the dashboard that tracks it.

  • Define the platform surface: the APIs, configuration and admin experiences that app-layer PMs, forward-deployed engineers and enterprise admins use to compose and tune agents, including per-enterprise adapters and fine-tuning hooks.

  • Run a weekly ship cadence with GenAI and engineering, with enablement and customer success looped in before every release.

  • Write the specs engineers want to build from (data models, state machines, API shapes and the tradeoffs between them), and prototype in code or no-code tools before you write the doc.

What You’ll Bring

Required

  • 5+ years of product management, including at least 2 years shipping LLM-based agents to production users. You've owned a product where the model's behavior was the product.

  • Hands-on with the agent stack: tool calling, planning loops, memory and retrieval, multi-agent handoff patterns, and the ways each one fails. You can read a trace and tell us what went wrong.

  • You've built or owned an eval harness and used it to gate releases. You think in task success rates, not vibes.

  • Experience at an AI-native company, or on a large platform team paired with founder or early-stage startup experience, preferred. We're not looking for SaaS feature PMs.

  • Technical enough to spec data models, state machines and API shapes, and to explain the tradeoffs between them.

  • Comfortable deciding with incomplete data and shipping weekly. You'd rather fix a v1 in production than polish a v2 in a doc.

  • Clear writing. Your PRDs are short, your eval reports have numbers, and your Slack messages make sense to sales.

Preferred

  • Fine-tuning or RL exposure: SFT, DPO or reward-based training on outcome-labeled data, or per-tenant adapters.

  • Voice or real-time conversational agents, where latency and interruption handling shape the product.

  • GTM domain depth: you've carried a quota, run a CS book, or built for people who did.

  • Workflow or orchestration products at the platform level.

  • Enterprise platform experience: admin surfaces, permissions, audit, and the customers who ask for them.

The salary range for this position is $185,000 to $260,000. The compensation package for this position also includes stock options and company-paid benefits.

1mind's total compensation package is designed to be competitive and includes base salary, equity, and a full range of benefits and perks. Final compensation will depend on factors such as your skills, experience, qualifications, and location, and will be determined during the interview process. The hiring manager will share more details about the full compensation package and benefits as you move through the process.

We believe in providing interesting and meaningful work in a supportive and inclusive environment - free from discrimination for everyone without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, or veteran status. If you are passionate about learning and excited about what we are doing, then we want to hear from you!

[Please note that all legitimate communication from 1mind will come only from email addresses ending in @1mind.com. We will never ask for payment, financial information, or personal details outside of our official application process. If you receive a suspicious message, please disregard it and alert us at [email protected]]

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, notetaking, or summarizing responses. These tools assist our recruitment team but do not replace human judgment - all hiring decisions are made by people. If you would like more information about how your data is processed or prefer to opt out of any AI-assisted tools, please let your recruiter know. Opting out will not impact your experience or consideration.

#LI-Remote

Skills Required

  • 5+ years of product management experience, including at least 2 years shipping LLM-based agents to production users
  • Experience owning a product where model behavior was the product
  • Hands-on experience with tool calling, planning loops, memory and retrieval, multi-agent handoffs, and agent failure modes
  • Ability to analyze agent execution traces and diagnose issues
  • Experience building or owning an evaluation harness and using it to gate releases
  • Experience at an AI-native company or on a large platform team paired with founder or early-stage startup experience
  • Technical ability to specify data models, state machines, and API shapes and explain tradeoffs
  • Comfort making decisions with incomplete data and shipping weekly
  • Strong written communication skills, including concise PRDs and quantitative evaluation reports
  • Exposure to fine-tuning or reinforcement learning, including SFT, DPO, reward-based training, or per-tenant adapters
  • Experience with voice or real-time conversational agents, latency, and interruption handling
  • Go-to-market domain experience, such as carrying a quota, managing a customer success book, or building for GTM users
  • Experience with workflow or orchestration products at the platform level
  • Enterprise platform experience with administration, permissions, and audit capabilities

1mind Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about 1mind and has not been reviewed or approved by 1mind.

  • Fair & Transparent Compensation — Pay is considered competitive with clear employer-provided salary bands across key roles, signaling transparency on base ranges. These ranges align with upper‑market startup compensation in the SF Bay Area.
  • Strong & Reliable Incentives — Incentive structures include bonuses and, for sales roles, commissions that complement base pay. Variable components are presented as standard elements of total compensation for go‑to‑market positions.
  • Equity Value & Accessibility — Equity is broadly included alongside cash compensation, making ownership accessible across multiple roles. Equity is framed as a core part of the total compensation package.

1mind Insights

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The Company
100 Employees
Year Founded: 2024

What We Do

1mind is a platform that deploys multimodal AI-powered Superhumans for revenue teams. These Superhumans combine a face, a voice, and a GTM brain, equipped with deep technical and product knowledge, to lead unlimited, simultaneous conversations 24/7, qualifying leads, booking meetings, and driving measurable impact.

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