Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values – Collaborative, Responsible, Entrepreneurial, Self-Aware, Trustworthy – and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry.
Job Description
SUMMARY
Ares Management is seeking a highly motivated Senior Associate, AI Engineer to help build and operate the firm's enterprise AI platform and production AI capabilities supporting use cases across investment and corporate functions.
This is a hands-on engineering role within the central Data & AI organization. The Senior Associate will work with experienced AI engineers, platform engineers, data engineers, product managers, and business-aligned technology teams to design and deliver production-quality AI services and applications.
The successful candidate will combine strong software engineering fundamentals with practical experience developing Generative AI and machine learning solutions. They will contribute to shared platform capabilities such as model access, retrieval, agentic workflows, evaluation, APIs, observability, and developer tooling, while also helping product and application teams bring AI use cases from prototype through production.
This role is well suited for an engineer who wants to work across modern AI technologies while developing deep experience in enterprise-grade architecture, security, governance, reliability, and software engineering.
REPORTING RELATIONSHIPS
Reports to: AI Platform & Engineering leadership
PRIMARY FUNCTIONS & RESPONSIBILITIES
AI Engineering
Design, develop, test, and operate production-grade AI services and applications.
Write clean, maintainable, well-tested production code using Python and modern software engineering practices.
Develop APIs, services, libraries, and reusable components that support AI applications across the firm.
Participate in technical design, code reviews, testing, troubleshooting, and production support.
Work with senior engineers to implement platform architecture, engineering standards, and reusable design patterns.
Own defined engineering components and workstreams from development through deployment and ongoing operation.
Generative AI & Shared AI Services
Build Retrieval-Augmented Generation capabilities using embeddings, semantic search, hybrid retrieval, vector databases, document processing, and structured data retrieval.
Develop reusable services for document extraction, search, retrieval, and AI-powered workflows.
Build agentic and multi-step workflows incorporating model reasoning, tools, enterprise data, and application services.
Implement prompt templates, structured outputs, tool-use patterns, and reusable orchestration components.
Build integrations using Model Context Protocol and other AI interoperability patterns where appropriate.
Contribute to evaluation frameworks for measuring retrieval quality, generation accuracy, workflow performance, and overall AI-system quality.
Experiment with emerging models, frameworks, retrieval techniques, and AI engineering approaches and help translate successful experiments into production capabilities.
AI Platform Development
Contribute to enterprise AI gateway capabilities supporting model access, routing, resiliency, usage tracking, and cost management.
Develop common APIs and SDKs that make AI platform capabilities easy for other engineering teams to consume.
Support prompt management, model configuration, model lifecycle, and deployment capabilities.
Integrate AI services with enterprise data products, applications, APIs, and internal systems.
Help build reusable tooling and reference implementations that accelerate…