AI Product Manager

Rezolve Ai; Greater London; On-site; GBP 75,000 - 95,000; Full time

Job summary

A leader in AI solutions in the Greater London area seeks an experienced AI Product Manager. In this high-impact role, you'll own the evaluation, quality, and deployment of AI across the Conversational Commerce platform. Responsibilities include defining evaluation strategies, ensuring safe AI behavior, and overseeing AI capabilities that add customer value. The ideal candidate has 4–7 years of experience in Product Management or Applied AI and is a clear communicator across technical teams. Join to shape innovative AI-driven experiences.

Qualifications

• 4–7+ years in Product Management, Applied AI, or ML-adjacent roles.
• Hands-on experience shipping LLM-powered systems in production.
• Strong understanding of LLM failure modes, evaluation techniques, and mitigation strategies.

Responsibilities

• Own the evolution of AI capabilities within Conversational Commerce.
• Define AI evaluation strategy and success metrics.
• Contribute to decisions on LLM deployment across conversational flows.

Skills

Product Management

Applied AI

Machine Learning

Communication

Job description

About Rezolve AI

Rezolve Ai (NASDAQ: RZLV) is an industry leader in AI-powered solutions, specializing in enhancing customer engagement, operational efficiency, and revenue growth. The Brain Suite delivers advanced tools that harness artificial intelligence to optimize processes, improve decision-making, and enable seamless digital experiences

As a leader in Product Discovery, we empower retailers and brands with AI-driven search, conversational commerce, geofencing, and one-touch instant payments. With recent acquisitions of ViSenze, GroupBy and Bluedot, Rezolve is accelerating innovation at the intersection of AI, commerce, and customer engagement

About the Role

We are hiring an AI Product Manager to own the evaluation, quality, and safe deployment of AI across Rezolve’s Conversational Commerce platform.

You will define how LLMs and agentic systems are used in production, set guardrails and quality standards, and own/go–no decisions for AI-driven changes. You will work closely with Product, Engineering, and AI teams to ensure Conversational Commerce delivers trusted, enterprise‑ready AI experiences.

This is a high‑impact role with influence across product strategy, architecture, and execution.

Responsibilities

AI Product Ownership & Strategy

Own the evolution of AI capabilities within Conversational Commerce.

Define how conversational and agentic AI translate into differentiated customer value.

Partner with the Principal PM to shape roadmap priorities, sequencing, and trade‑offs.

AI Evaluation, Quality & Decision Ownership

Own the AI evaluation strategy, including:

• Success metrics
• Experiments and analysis
• Tying model performance to user and business outcomes
• Define and track core AI quality metrics (e.g. task success, hallucinations, latency).

Own go/no-go decisions for AI changes (ship, rollback, iterate).

Clearly communicate impact, risk, and trade‑offs to Product, Engineering, and Leadership.

Model Safety & Guardrails

Own LLM safety testing

Define and evolve guardrails to ensure safe, reliable AI behaviour.

Partner with engineering on grounding strategies, constraints, fallbacks, and escalation paths.

Ensure AI systems are observable and improve over time.

Conversational & Multi‑Agent Systems

Contribute to decisions on how LLMs are deployed across conversational flows.

Help shape the Conversational Commerce multi-agent framework, including:

• Agent roles and responsibilities
• Orchestration and task decomposition
• Tool usage boundaries

Ensure agentic systems are testable, debuggable, and scalable.

Discovery & Execution

Lead continuous discovery through customer research, usage analysis, and feedback loops.

Validate that AI capabilities solve real, high‑impact customer problems.

Translate AI strategy into clear requirements, roadmaps, and prioritized backlogs.

Enable fast execution without compromising quality or trust.

About You

Essential

• 4–7+ years in Product Management, Applied AI, or ML‑adjacent roles
• Hands‑on experience shipping LLM‑powered systems in production.
• Strong understanding of LLM failure modes, evaluation techniques, and mitigation strategies.
• Comfortable making trade‑offs across capability, cost, latency, and risk.
• Clear, confident communicator across technical and non‑technical teams.

First 6 months

• Clear AI evaluation and quality framework adopted across Conversational Commerce.
• Defined guardrails and safety standards enforced in production.
• Stable, observable conversational and agentic flows operating at scale.
• Confident go/no-go decision‑making for AI changes.
• Strong alignment across Product, Engineering, AI, and Commercial teams.