AI Infrastructure Engineer

Hedge Fund; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Hedge Fund in New York is seeking an experienced AI Platform Engineer to design, build, and scale the foundational infrastructure that enables AI-driven development across the organization. You will focus on secure, production-grade systems supporting intelligent agents, LLMs, and distributed AI tooling, combining strong software engineering with hands-on AI infrastructure and SRE practices.

The role collaborates with multiple teams to implement governance, security controls, and scalable

Qualifications

• 5+ years of professional software engineering experience.
• Proven ability to design scalable, production-grade systems.
• Experience managing Kubernetes in production.
• Expertise in AI/ML infrastructure and agent-based platforms.

Responsibilities

• Design and build orchestration frameworks for LLM-powered tools.
• Develop scalable AI infrastructure for distributed teams.
• Manage agent lifecycles and enforce security standards.
• Build MCP services for enterprise system integration.
• Implement governance, observability, and risk controls.
• Partner with teams to promote AI infrastructure adoption.

Skills

5+ years exp

Kubernetes

AI/ML infra

Security architecture

OAuth 2.0

Job description

Multi-Strategy / Multi-Manager hedge fund is seeking an AI Platform Engineer to design, build, and scale the foundational infrastructure that enables AI-driven development across the organization. This role will focus on building secure, production-grade systems that support intelligent agents, large language models (LLMs), and distributed AI tooling. The ideal candidate combines strong software engineering fundamentals with hands-on experience in AI infrastructure and Site Reliability Engineering (SRE) experience.

Responsibilities:

• Build Intelligent Agent Platforms: Design and implement orchestration frameworks and secure execution environments that enable LLM-powered tools and agent-based workflows.
• Architect AI Infrastructure: Develop scalable infrastructure that supports distributed agent development and deployment across multiple teams and business units.
• Oversee AI Agent Operations: Manage agent lifecycles and ensure AI-generated outputs — including code — align with architectural standards, security policies, and engineering best practices.
• Develop Agent Communication Systems: Build and maintain Model Context Protocol (MCP) services and supporting infrastructure to enable reliable communication, coordination, and integration with enterprise systems.
• Implement Governance & Security Controls: Establish monitoring, observability, compliance, and security frameworks to ensure safe and responsible AI operations at scale.
• Drive Organizational Adoption: Partner directly with teams across the firm to promote AI infrastructure best practices, provide hands-on guidance, and support adoption of AI-augmented development workflows.

Requirements:

• 5+ years of professional software engineering experience, with a proven track record of designing and delivering scalable, production-grade systems.
• Demonstrated experience managing Kubernetes in a production environment.
• Expertise in building and supporting AI/ML infrastructure, agent-based systems, or AI-enhanced developer platforms.
• Solid understanding of modern security architecture, including API security, OAuth 2.0 and Keycloak authentication flows, and secure system design principles.

Nice to haves:

• Hands-on experience with AI agent frameworks, LLM integrations, or Model Context Protocol (MCP) implementations.
• Experience designing multi-tenant or federated AI platforms operating across distributed environments.
• Familiarity with enterprise AI governance, compliance frameworks, and operational risk controls.
• Background in cybersecurity, security architecture, or penetration testing.
• Experience working with AI-assisted development tools, automated code generation, and modern testing frameworks.