Senior Product Manager, Recruitee

• We are looking for a seasoned product leader who possesses the technical depth to hold their own with AI engineers, paired with the product judgment to know what not to build
• You lead with a bias to ship the smallest possible thing that proves the next strategic bet
• Significant experience as a Product Manager, with a proven track record of shipping production-grade AI/agentic products or developer tooling
• Strong technical fluency in LLMs, agent architectures, MCP-style patterns, and LLM evaluation methodologies
• Comfort navigating multi-cycle, cross-product initiatives where the ultimate destination is clear but the discovery path requires exploratory iteration
• Exceptional written and asynchronous communication skills. With a remote-first collaboration model across offices, documentation and clear writing are your primary levers
• High product judgment and a strong commercial mindset - you think in terms of adoption and customer value, not just technological capability
• Full professional proficiency in English (C1 level)

Desirable

• As our Senior Product Manager for the Agentic initiatives, you will own Tellent’s transition from a System of Record to a System of Action
• This is a high-impact, cross-product role: instead of being embedded in a single product team, you will operate across all three of our core products - Hire, Manage, and Grow - building the unified AI layer that connects them
• You will own the agentic product strategy and multi-cycle roadmap, driving everything from Model Context Protocol (MCP) infrastructure and specialist agents (Help, Hiring, Analytics) to action execution and external ecosystem channels like Slack and mobile
• This is an execution-heavy role for a technically fluent product leader
• You will act as the primary product contact for an AI/LLM-native engineering team, collaborating deeply on agent architectures, evaluation loops, and quality frameworks
• You will also partner with our exploratory AI workstream to integrate long-term vision into concrete, shippable increments
• You will report directly to our Chief Product Officer (CPO) and work day-to-day with our AI Engineering Team Lead
• Your 12-month journey:
• First 3 months: Immerse yourself in the existing capabilities of Hire, Manage, and Grow. Establish a trusted operating cadence with the AI engineering team and build alignment with product PMs across our core areas. Deliver structural clarity to the immediate cycle work and take over the execution of our foundation layer
• After 6 months: Ship the foundational MCP infrastructure alongside our first wave of specialist agents (Help, Hiring, Analytics) into production. Establish clear evaluation methodology and quality loops to measure and define agentic adoption, moving from exploratory paths to predictable delivery
• After 1 year: The agentic foundation is adopted and driving measurable value across our customer base. You have mapped out a legible multi-cycle roadmap extending to proactive suggestions and external channels, validated early agentic monetization hypotheses, and successfully secured active production design partners within the AI-native segment
• What you’ll be doing:
• Product strategy & cross-product roadmap: Own the agentic product lifecycle across Hire, Manage, and Grow. Ensure the AI layer acts as a cohesive fabric rather than isolated features, maintaining constant alignment with core product PMs
• AI engineering partnership: Act as the direct product counter-weight to a highly technical, LLM-native engineering team. Collaborate on agent architectures, tooling, eval loops, and engineering tradeoffs
• Vision execution: Bridge the gap between blue-sky AI possibilities and reality. Partner with our exploratory AI workstream to ingest strategic vision and translate it into a pragmatic roadmap with clear execution metrics and kill criteria
• Market & monetization tracking: Keep a pulse on the rapidly evolving agentic HR landscape (both AI-native startups and pivoting incumbents). Inform our Ideal Customer Profile (ICP) direction and test pricing hypotheses, including per-agent monetization models
• Defining "Good": Establish and track adoption metrics that signal a successful transition to a System of Action, providing clear signals that leadership and the GTM teams can act upon