Product Manager — AI Products

Role Description

This is a Product Manager role for people who build, not just specify. Two things are equally true about how we work, and both are non-negotiable expectations of this role:

• The products you own are agent systems, and they are non-deterministic. Your design surface includes:
  • Prompts
  • Tool definitions
  • Retrieval strategy
  • Schema contracts
  • Model selection
  • Fallback behavior
  • Failure modes
• You use these models to do the product work, which includes:
  • Writing specs
  • Generating structured data
  • Producing working HTML prototypes
  • Running evaluation batches
  • Analyzing output quality

What you'll actually do:

• Own one or more product lines — outcomes, roadmap, sequencing, and the quality bar
• Write the spec set engineering builds from: product spec, engineering spec, model spec, and handoff readiness — decisions resolved, not deferred
• Design the agent behavior — prompt architecture, output schemas, deterministic vs. model-decided logic, guardrails, and what happens when the model is wrong or the tool call fails
• Build prototypes yourself — working HTML with live model calls, ahead of engineering commitment
• Define and run evaluations — build eval sets, score output batches, set ship/no-ship thresholds
• Make the model tradeoffs — model choice, context strategy, latency, token cost per unit of output
• Work directly with engineering, GenAI, and design on daily execution
• Interface with customers and enterprise partners, including US-based partners with real security, privacy, and compliance review processes
• Instrument and read the data — usage, quality, cost, and drift — and act on it

Qualifications

• 4+ years in product management, ideally B2B SaaS
• Demonstrated hands-on work with LLM / agent products: prompt design, structured output, retrieval, tool/function calling, evaluation
• Fluency using AI tooling in your own workflow — specs, prototypes, analysis, code reading
• Ability to read code and API contracts well enough to review a schema, follow a pipeline, and spot a bad interface
• Track record of shipping — features live, in customers' hands, with measured outcomes
• Strong written communication; ability to communicate technical decisions to both a CEO and an engineer
• Comfort operating with ambiguity and short cycles

Requirements

• Preferred degree in AI/ML, Engineering, CS, or a related technical field
• Direct experience with OpenAI, AWS Bedrock, Anthropic/Claude, LangChain, or equivalent orchestration stacks
• Experience with voice AI, agentic workflows, or multi-agent systems
• Experience with fine-tuning, dataset curation, or model performance analysis
• Experience working with US customers and enterprise partners
• SMB or marketing-technology domain knowledge

Benefits

• Fully remote
• Genuine ownership of a product line, with the latitude to shape it
• Work at the current frontier of applied AI product development — agent systems, evals, voice, and multi-model orchestration in production
• A small, high-context team that moves quickly and argues about the work
• Real impact on the small businesses our customers serve