Principal Forward Deployed Data Scientist

About the role

This senior, hands‑on technical leadership position focuses on building production AI applications that move from prototype to reliable, scalable systems within a regulated environment. You will work directly with business stakeholders to define problems, design solutions, and deliver autonomous AI agents that serve internal and customer‑facing needs.

Key responsibilities

• Take ideas from prototype to production, delivering reliable, scalable AI systems.
• Design, implement, deploy, and evolve end‑to‑end agentic AI that reasons, plans, calls tools, and acts on behalf of users.
• Build agent‑orchestration architectures, including multi‑agent coordination, tool/function calling, memory, and safety mechanisms.
• Assess each problem and select the appropriate model, agent pattern, or architecture.
• Stay on the bleeding edge of new models and frameworks, quickly prototyping and bringing production‑ready innovations forward.
• Ship software on time while meeting governance, risk, compliance, and audit requirements of a regulated environment.
• Embed with business teams, translate goals into AI capabilities, and set technical standards for responsible AI.

Required profile

• Proven experience delivering production AI/LLM applications used by internal or external customers.
• Demonstrated ability to move from fast proof‑of‑concept to hardened, maintainable production systems.
• Track record of shipping software in regulated sectors such as financial services.
• Hands‑on experience with agentic AI, including multi‑agent coordination and safety controls.
• Strong software engineering fundamentals: reliability, observability, testing, and maintainability.
• Excellent communication skills to bridge business conversations and technical design.
• Forward‑deployed mindset comfortable with ambiguity and focused on shipping value.

Required skills

• Building AI/LLM applications in production.
• Agentic AI development (reasoning, planning, tool calling, autonomous actions).
• Identity and access management for AI agents.
• Software engineering best practices (observable, testable, maintainable code).
• Experience with regulated‑environment compliance and governance.