Senior Engineer, AI Platform Engineering
Ares Management Corporation3 days ago
Mumbai, IndiaMid Level / Senior
Responsibilities
- Design, develop, test, deploy, and operate production-grade AI services and applications using Python.
- Develop APIs, services, SDKs, libraries, reusable components, and reference implementations for shared AI capabilities.
- Build RAG, semantic and hybrid retrieval, vector search, document-processing, structured-data retrieval, and AI-powered workflow solutions.
- Create agentic and multi-step workflows using model reasoning, tools, enterprise data, application services, prompts, structured outputs, and orchestration components.
- Contribute to enterprise AI gateway capabilities for model access, routing, resiliency, usage tracking, cost management, prompt management, and model lifecycle operations.
- Integrate AI services with enterprise data products, applications, APIs, internal systems, and governed data sources.
- Build CI/CD pipelines, automated testing, monitoring, telemetry, logging, tracing, rollback mechanisms, and production-support capabilities.
- Implement secure authentication, authorization, secrets management, encryption, entitlement-aware data access, and AI governance controls.
- Troubleshoot production issues, participate in root-cause analysis, monitor service performance and quality, and contribute to reliability improvements.
- Partner with product managers, data engineers, application developers, cybersecurity teams, and business stakeholders to deliver AI use cases.
- Create documentation, examples, reusable patterns, and tooling that help other engineering teams adopt shared AI capabilities.
Requirements
- Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related technical discipline.
- 4 to 8 years of professional software engineering, data engineering, machine learning engineering, or related experience.
- Hands-on experience developing machine learning, Generative AI, LLM, or data-intensive applications.
- Strong Python development skills and experience writing production-quality software.
- Experience designing or consuming APIs, services, and cloud-based applications.
- Experience with a major cloud platform, preferably Azure.
- Practical experience with Generative AI techniques such as RAG, embeddings, vector search, prompt engineering, structured generation, tool use, or agentic workflows.
- Familiarity with Git, automated testing, CI/CD, containers, and production monitoring.
- Strong problem-solving, debugging, ownership, written communication, and collaboration skills.
- Preferred experience with Databricks, Delta Lake, Unity Catalog, Model Serving, MLflow, or Vector Search.
- Preferred experience with Azure OpenAI, Azure AI services, OpenAI, Anthropic, or comparable enterprise LLM providers.
- Preferred experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, or comparable LLM application and agent frameworks.
- Preferred experience building RAG applications, document-processing pipelines, semantic or hybrid search, vector-search solutions, or LLM evaluation systems.
- Preferred familiarity with Model Context Protocol, function calling, tool-use patterns, agent interoperability, LLM observability, tracing, production monitoring, and AI cost management.
- Experience in financial services, regulated environments, asset management, private equity, investment banking, or alternative investments is preferred.
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About Ares Management Corporation
Ares Management Corporation is a global alternative investment manager that raises and manages funds across credit, private equity, real estate, and infrastructure for institutional and individual investors. It earns management and performance fees by investing and providing direct lending and other financing solutions to businesses and assets worldwide. Founded in 1997 and headquartered in Los Angeles, Ares is a publicly traded company on the NYSE (ticker: ARES) with operations across multiple continents.