Senior AI Product Manager

Senior Product Manager, Bazak

Ramat Gan (Bursa) · Hybrid: 3–4 days in the office

About Bazak: The Operating System for AI Commerce

More and more consumers use AI to buy products, and brands need to close those deals themselves instead of becoming a static catalog for LLMs. Bazak turns a brand’s website into a live AI operating system: one agent that sells in ChatGPT, Claude and on the brand’s own site, then serves the customer after the purchase, with no engineering needed on the client side.

Over 40% of sessions end in a completed outcome: a booking, a lead or a resolved request. Our customers include publicly traded companies running at high scale.

The Role

• You’ll own the Bazak platform as a product: what it does, what it doesn’t do, and in what order we build it. This is a hands-on role. Our product is an AI agent platform: MCP tools, LLM orchestration, evals, integrations and analytics.
• You’ll need to understand it at the level of the engineers who build it.
• This isn’t a customer delivery role. You might assist individual brand deployments. Your job is to build the product that makes every deployment faster, better and repeatable, and to decide what goes into the core platform and what stays out.
• You’ll report to CEO and work daily with the engineering team.

What you’ll do

• Own the product roadmap for the platform. Set priorities, make trade-offs explicit, and say no to one-off requests that don’t serve the product.
• Own your product areas from problem to outcome: discovery, spec, delivery with engineering, and measuring results after launch. Shipping isn’t the finish line. A verified result is.
• Write clear, testable specs covering user flows, agent behavior, tool contracts, edge cases, acceptance criteria and success metrics.
• Go deep on the technology. Understand our MCP tools and contracts, and reason about LLM behavior, latency and cost trade-offs.
• Design the platform’s quality system: the eval framework, guardrails and the feedback loop that turns production failures into product improvements across all verticals.
• Do your own data work. Query product analytics and run SQL across the customer base to find patterns, size opportunities, and design and read experiments.
• Find patterns across customers. Turn requests from many brands into general platform capabilities and self-serve configuration, not custom work.
• Prototype with AI tools. Use Claude, ChatGPT and AI coding tools to mock flows, test prompts and validate ideas before engineering time is spent.
• Run a disciplined process. Keep the backlog in Linear well groomed and prioritized, set a clear delivery cadence, and communicate decisions.

Must-have

• 8+ years in product management, with at least 4 owning a technical B2B platform.
• A technical background: You can understand system architecture and go deep with engineers on trade-offs. Past work as a software engineer or analyst, or equivalent hands-on experience.
• Hands-on experience shipping LLM or AI-agent products to production, including working knowledge of tool calling, prompting, RAG and evals.
• Strong product judgment. You have a track record of turning many customers’ needs into one coherent product, and of deciding what not to build.
• Strong SQL and analytics skills. You pull and analyze data yourself, without waiting on an analyst.
• A track record of specs and delivery processes that engineering teams rely on, with concrete examples of features you owned from idea through measured outcome.
• Comfortable using AI coding and prototyping tools in your daily work.
• Excellent English.

Nice-to-have

• Experience building or integrating MCP servers, ChatGPT apps or Claude connectors.
• Experience in e-commerce, travel or hospitality, or with conversion optimization.
• Familiarity with PostHog or similar product analytics and LLM observability tools.
• Experience as an early or founding PM, taking a product from 0 to 1 and on to scale.