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Salary: USD 185,000 - 260,000 / annual
1Mind is building Autonomous Customer Experience software—a new category of enterprise platform that deploys AI-powered "Superhumans" to handle go-to-market work (SDR, SE, onboarding, account management, customer success) across the entire buyer journey with continuous memory and context.
You will own the agent runtime and orchestration layer—the first dedicated PM seat for this critical infrastructure. You'll report to the Chief Product Officer and work directly with the GenAI engineering team to define how agents plan, call tools, share memory, hand off work to each other, and get evaluated.
Key responsibilities:
- Own the agent runtime that powers every Superhuman: planning algorithms, tool calling, memory reads/writes against a context graph, guardrails, and the Assist/Co-pilot/Autonomous trust ladder.
- Design multi-agent orchestration: handoffs between Superhumans across the customer journey (inbound SDR → SE → onboarding → CSM), shared state management across deals/accounts, and conflict resolution when multiple agents target the same contact.
- Productize GTM orchestrations: create packaged plays by funnel stage (qualification, activation, retention, expansion) that customers configure rather than build from scratch. Define primitives: triggers, steps, agent assignments, human checkpoints.
- Build and own the evaluation harness for agent behavior: task-level success rates, objection-to-advance metrics, escalation precision, hallucination rates, tool-error rates. Set release gates and own the tracking dashboard.
- Define the platform surface: APIs, configuration UX, and admin experiences for app-layer PMs, forward-deployed engineers, and enterprise admins to compose and tune agents. Include per-enterprise adapters and fine-tuning hooks.
- Execute a weekly ship cadence with GenAI and engineering; loop in enablement and customer success before every release.
- Write specs engineers want to build from: data models, state machines, API shapes, and tradeoffs. Prototype in code or no-code before writing formal docs.
The window is short—large platforms are consolidating the funnel ends, but the live-conversation middle remains open. Expect to ship a rough v1, then iterate weekly.
REQUIREMENTS:
Required:
- 5+ years of product management, with at least 2 years shipping LLM-based agents to production users. You've owned a product where model behavior was the core product.
- Hands-on with the agent stack: tool calling, planning loops, memory/retrieval, multi-agent handoff patterns, and failure modes. Can read execution traces and diagnose issues.
- Built or owned an eval harness and used it to gate releases. Think in task success rates, not intuition.
- Experience at an AI-native company OR on a large platform team paired with founder/early-stage startup experience (preferred). Not looking for traditional SaaS feature PMs.
- Technical depth: can spec data models, state machines, API shapes, and explain tradeoffs.
- Comfortable deciding with incomplete data and shipping weekly. Prefer fixing v1 in production over polishing v2 in docs.
- Clear writing: short PRDs, eval reports with numbers, sensible Slack communication.
Preferred:
- Fine-tuning or RL exposure: SFT, DPO, reward-based training on outcome-labeled data, or per-tenant adapters.
- Voice or real-time conversational agents (latency and interruption handling shape product).
- GTM domain depth: carried quota, run CS book, or built for people who did.
- Workflow or orchestration products at platform level.
- Enterprise platform experience: admin surfaces, permissions, audit, customer requirements.
