Principal Product Manager (AI)

TL;DR

Principal Product Manager (AI): Owning MLOps and Agentic strategy for hirify.global’s Analytics Platform with an accent on model governance, risk management, and ensuring AI systems meet regulatory expectations. Focus on shaping roadmaps, influencing architecture, and driving adoption across engineering, risk, compliance, and business stakeholders.

Location: UK - Remote / UK - Belfast / UK - London

Salary: £0 - £0 a year

Company

hirify.global empowers its customers to manage risk and unleash intelligence in their digital communications.

What you will do

• Define and socialize the multi-year MLOps platform roadmap, spanning model training, evaluation, deployment, monitoring, and retirement across global regions.
• Architect product solutions for multi-region model inference with data residency constraints.
• Drive model observability and drift detection capabilities in partnership with Data Science and Engineering.
• Publish the Agent Framework Reference Architecture defining how autonomous and semi-autonomous agents are designed, tested, and deployed within a regulated FinServ environment.
• Champion model governance as a product capability by embedding risk controls directly into the platform.
• Partner with Applied ML, Engineering, Product, Finance, and Procurement to ensure alignment on strategy, performance, and cost.

Requirements

• 8+ years of product management experience, with at least 3 years focused on ML infrastructure, MLOps platforms, or AI/ML product strategy.
• Experience partnering directly with Data Science/Applied ML and Engineering teams.
• Demonstrated experience shipping ML platform or AI infrastructure products in a regulated industry.
• Hands-on experience/ strong familiarity with MLOps tooling (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, Databricks).
• Working knowledge of LLM orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen, CrewAI).
• Excellent communication skills and ability to work across product, engineering, and commercial teams.

Nice to have

• Experience with regulated industries or enterprise SaaS.
• Engineering or data science background.
• Understanding of model risk management (MRM) frameworks and how they apply to modern ML and LLM systems in financial services.

Culture & Benefits

• Bonus and stock options available.
• Private Health Insurance, Employee Dental Plan, and Group Life Assurance (GLA).
• Wellness Reimbursement and Internet Allowance.
• Pension employer match.