Lead Decision & AI Scientist

Overview

In this role you join MPB’s AI Automation Hub as the data and decision brain, turning ideas into production-ready agentic AI tools. You will build evaluation sets, scorecards and guardrails, and establish robust data foundations to support trustworthy AI systems. Working alongside a peer-led team, you’ll evaluate experiments, coach other teams, and determine whether to advance, adjust or sunset initiatives. You’ll influence how AI is responsibly deployed across the business and showcase measurable value.

Responsibilities

• Turn ideas into time-boxed, production-ready experiments
• Create evaluation sets, scorecards, and guardrails for AI systems
• Develop data foundations and retrieval mechanisms to support agentic workflows
• Evaluate experiments and communicate findings to stakeholders, guiding next steps
• Collaborate as a peer within the Hub and coach cross-functional teams on responsible AI
• Balance exploration with practical delivery, ensuring human oversight where needed

Key requirements

• Substantial hands-on experience in data science, ML or applied AI
• Experience with agentic workflows, multi-agent systems or production LLM applications
• Evaluation engineering: eval sets, scorecards, regression tests and guardrails for non-deterministic systems
• Strong, production-quality Python and the modern AI toolkit
• Cloud data experience, including BigQuery and at least one production ML/AI platform (e.g., Vertex AI)
• Ability to explain findings clearly to exec-level audiences and to coach non-technical teams
• Clear, executive-level communication
• Coaching and cross-functional collaboration
• Problem-solving mindset with emphasis on responsible AI
• Python (production-grade)
• LLM frameworks
• Vector stores

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