AI Lead

About the Role

AI & ML Lead

AI engineering, ML systems, and business-critical decisioning

set the technical bar

not a research role

how AI behaves in production

Key Responsibilities

• Own the end-to-end architecture of AI & ML systems across Neo
• Define

  agentic, decision-driven AI patterns

  (rules + ML + LLMs)
• Review and approve models before they enter production
• Set standards for evaluation, monitoring, and failure handling
• Guide AI Engineers and ML Engineers on system design and trade-offs
• Partner closely with Product, Risk, Compliance, and Engineering leaders
• Ensure AI systems meet

  latency, trust, and auditability requirements

• Take final ownership during incidents involving AI/ML behavior

Required Skills & Experience

• 6+ years building

  production-grade AI / ML systems

• Strong system design and architectural thinking
• Experience with real-time decision or scoring systems
• Proven ability to debug and stabilize AI systems in production
• Experience leading technical teams or acting as a tech bar-raiser

Good to Have

• Experience in fintech, trading, or regulated domains
• Background in risk, fraud, or decision engines
• Exposure to agentic AI or complex workflow systems
• Experience working with compliance, audit, or governance teams

What We Value

• Engineers who think in

  systems, not models

• Strong judgement under ambiguity
• Bias toward reliability and trust over novelty
• Ability to raise the bar without slowing teams down
• Ownership mindset -

  AI outcomes are your outcomes

Role Expectations (Important)

no