AI Platform Lead

What you'll do

• Own the AI platform roadmap and end-to-end architecture, guiding implementation, adoption, and ongoing operation.
• Lead development of shared AI services, agent frameworks, developer tooling, and capabilities for evaluation, observability, security, and reliability.
• Build and mentor the platform engineering team and partner with internal teams and senior stakeholders to drive adoption and delivery.

What they ask for

• 10+ years of experience in software engineering, platform engineering, infrastructure, or distributed systems, including senior technical leadership.
• Experience leading engineering teams and owning shared platforms or infrastructure used by multiple teams; track record delivering complex capabilities into production and operating them.
• Strong understanding of LLMs, agentic systems, retrieval-augmented generation, model serving, and AI application architectures; hands-on software development expertise, particularly in Python.
• Deep experience with distributed systems, APIs, Kubernetes, containerization, cloud or hybrid infrastructure, and infrastructure automation; bachelor’s degree in a related technical discipline or equivalent practical experience.

Nice to have

• Experience in hedge funds, quantitative investment management, trading, or financial services; enterprise AI platforms or internal developer platforms.
• Hands-on experience with agent frameworks, MCP servers and gateways, AI evaluation, and MLOps/LLMOps; familiarity with high-performance computing, NVIDIA GPU infrastructure, and inference optimization.

Pay

USD $275,000 to $300,000 base salary

Tools

Python, Kubernetes, MCP servers and gateways, NVIDIA GPU infrastructure, MLOps/LLMOps

AI focus

Owns the shared AI platform, including model access and serving, agent frameworks and runtimes, retrieval, enterprise data integration, evaluation, observability, and secure deployment of AI applications.