Product Manager — AI Products

BuzzBoard

20h • Remote

About The Position

BuzzBoard builds AI products for the B2SMB market — helping agencies, media companies, and sellers understand small businesses and market to them at a level of personalization that wasn’t previously economical. Our platform is built on frontier models end to end. Not AI features bolted onto a legacy product — the products are agent systems. Our products span multi-agent marketing content generation, real-time AI voice intake, and pre- and post-sales intelligence for SMBs — Zylo, IRIS, Ignite, and Ember. They share a common internal pipeline for orchestration, retrieval, tool use, evaluation, and deployment, and a spec-driven development process that treats agent behavior as a first-class design artifact.

Requirements

• 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. We will ask you to walk through something you shipped in detail.
• 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; you can take a technical decision and make it legible to a CEO and to an engineer in the same document
• Comfort operating with ambiguity and short cycles

Nice To Haves

• 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

Responsibilities

• 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, so we argue about a thing instead of a document
• Define and run evaluations — build eval sets, score output batches, set ship/no-ship thresholds, and drive prompt and model iteration off measured results rather than vibes
• Make the model tradeoffs — model choice, context strategy, latency, token cost per unit of output, fine-tune vs. prompt vs. retrieval
• Work directly with engineering, GenAI, and design on daily execution; hold the line on schema and interface contracts between agents
• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed