Vice President, AI Engineer

Ares Management is seeking a highly motivated Vice President, AI Platform Engineering to help design, build, and scale the firm's enterprise AI platform and the production-grade AI capabilities that support use cases across the organization. This is a highly hands-on engineering role within the central Data & AI organization. The VP will design, build, and operate reusable AI platform services and work closely with AI Engineering, Data Engineering, Product Management, Cybersecurity, and business teams to bring AI solutions from concept through production.

The successful candidate will combine strong software engineering fundamentals with practical experience building Generative AI and machine learning systems. They will own significant platform components and technical work streams, contribute to architecture and engineering standards, and help enable development teams across the firm to build secure, scalable, reliable, and governed AI applications.

Reports to:

Managing Director, Head of Data Engineering & AI Platforms

• Design, build, and operate production-grade services supporting Ares' enterprise Generative AI platform.
• Own major platform components and technical work streams from design through implementation, deployment, and ongoing operation.
• Develop reusable APIs, SDKs, services, and developer tooling that enable teams across the firm to build AI applications efficiently.
• Contribute to platform architecture, technical standards, design patterns, and engineering best practices.
• Partner with senior AI engineering and architecture leaders on technical design decisions and platform evolution.
• Write high-quality production code and participate actively in design reviews, code reviews, testing, and troubleshooting.

• Build and enhance multi-LLM gateway capabilities supporting multiple model providers, including routing, rate limiting, resiliency, usage tracking, and cost management.
• Develop Retrieval-Augmented Generation services, including embeddings, semantic and hybrid search, vector database integrations, document processing, and structured retrieval.
• Build reusable orchestration services supporting agentic, multi-agent, and multi-step AI workflows.
• Develop and maintain prompt management, model registry, model lifecycle, and evaluation capabilities.
• Implement integrations using Model Context Protocol (MCP), agent tool-use patterns, and other emerging AI interoperability standards.
• Develop observability and AI Fin Ops capabilities to monitor quality, latency, token consumption, utilization, and cost.
• Integrate AI platform services with enterprise data products, applications, APIs, and other internal systems.

• Partner with AI Product Management, Data Engineering, and business teams to translate business requirements into scalable technical solutions.
• Enable secure connectivity between AI applications, enterprise systems, and governed data sources.
• Develop reusable patterns and platform services that accelerate delivery of AI use cases across investment and corporate functions.
• Support vertical engineering teams adopting shared platform capabilities and provide technical guidance on implementation.
• Create reference implementations, documentation, technical design artifacts, and development standards to promote consistent adoption.

• Build and maintain CI/CD pipelines for AI applications and platform services
• Implement monitoring, telemetry, performance measurement, and operational health dashboards
• Establish deployment processes, testing frameworks, and production support models
• Contribute to disaster recovery and high-availability strategies for…