AI Infrastructure Engineer

We see the world differently at Capstone Investment Advisors. You will, too. Capstone Investment Advisors, LLC (“Capstone”) is a global asset manager, dedicated to exploring alpha opportunities in derivatives and complementary strategies that persist across market cycles. With approximately $12.5 billion of AUM (as of May 1, 2026) and 306 employees, Capstone is headquartered in New York with offices in London, Amsterdam, Stamford, Los Angeles, Boston, Tokyo, Milan, Texas, and Maryland. Since 2004, through strategic insight, market-leading expertise, and advanced technology, we have sought to anticipate and harness the complexities of world markets, creating unique opportunities for our clients, team, and industry. With our sophisticated, global client base, we recognize that our success is deeply connected to real people. For that reason, we take a human approach to everything we do, focusing largely on collaborative performance. Our workflow and process are built around the belief that by sharing ideas, we achieve greater outcomes. This gives you greater access to resources, direct exposure to senior leadership, and new opportunities to experiment and innovate. Learn more about how you can be part of the disciplined collaboration and transcendent thinking as our AI Platform Engineer at Capstone Investment Advisors here. Overview: We are seeking an AI Infrastructure 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 and Impact: 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. Our future colleague has these skills: 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. Do you possess these Bonus Skills:. 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 too…