Head of AI Architecture and Strategy
Madison-Davis, LLC
A leading investment management organization is seeking an experienced Head of AI Architecture & Strategy to lead the architecture of its shared AI technology platform and contribute to its long-term technical direction.
This is a senior, hands-on position combining enterprise AI architecture, platform engineering, and technical leadership. The successful candidate will develop scalable, secure, reusable AI infrastructure supporting research, investment, and internal business teams.
Responsibilities
- Own the architecture of shared AI services, including model gateways, inference, agent runtimes, orchestration, and retrieval.
- Guide the engineering of AI platform capabilities, agent frameworks, MCP integrations, APIs, and reusable developer tools.
- Establish architectural standards, design patterns, and implementation guidelines.
- Evaluate AI technologies and contribute to platform strategy and roadmap development.
- Provide hands-on technical architecture, prototyping, engineering reviews, and implementation guidance.
- Ensure production platforms incorporate appropriate security, access controls, observability, evaluation, and reliability.
- Lead and mentor technical engineering teams while promoting adoption of shared platform capabilities.
- Work closely with software engineering, research, investment, infrastructure, cybersecurity, and technology leadership.
Role Requirements
- 10+ years of relevant engineering experience with senior technical leadership responsibilities.
- Deep hands-on architecture experience involving complex enterprise or shared platforms.
- Strong knowledge of LLMs, AI agents, RAG, model serving, and enterprise AI systems.
- Strong Python software development expertise.
- Experience with distributed systems, APIs, Kubernetes, containerization, and cloud or hybrid infrastructure.
- Proven engineering leadership and ownership of production technology platforms.
- Understanding of platform security, access management, reliability, and observability.
- Strong technical judgment, architecture decision-making, and stakeholder communication.
- Bachelor's degree in a related technical discipline or equivalent practical experience.
- Ability to work onsite in Midtown Manhattan four days per week.
Nice to Have
- Investment management, hedge fund, quantitative trading, or financial-services experience.
- Experience building enterprise AI or internal developer platforms.
- Agent frameworks, MCP, AI evaluation, and LLMOps/MLOps experience.
- GPU-backed infrastructure or inference optimization experience.
- Vendor or platform cost management and an advanced technical degree.
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