18 hours ago
Mumbai, IndiaSenior
Responsibilities
- Design, build, deploy, operate, and continuously optimize an enterprise AI automation platform supporting infrastructure operations.
- Develop scalable infrastructure and cloud automation solutions using Python, APIs, AI technologies, and RPA where appropriate.
- Build AI-powered workflows that reduce manual effort, improve operational efficiency, and enable self-healing infrastructure operations.
- Develop reusable automation frameworks, enterprise APIs, and services for automation initiatives.
- Integrate LLMs with enterprise systems through secure APIs and tool or function calling orchestration.
- Lead AI automation initiatives aligned with business priorities and infrastructure operations needs.
- Apply governance, security, audit, and compliance practices to production automation.
- Troubleshoot complex production issues, perform root cause analysis, and improve platform reliability.
- Mentor associate engineers and promote reusable frameworks, engineering best practices, and high-quality software delivery.
Requirements
- 7–11 years of experience in Automation Engineering, Infrastructure Automation, Cloud Automation, Platform Engineering, or AI Automation.
- Experience with Kubernetes, Linux, Windows, VMware, Cisco UCS, and networking fundamentals including L2/L3, DNS, load balancing, and IP management.
- Experience with Azure or Google Cloud Platform.
- Strong hands-on Python experience and experience with REST APIs and preferably FastAPI.
- Experience designing reusable automation frameworks and enterprise APIs.
- Hands-on experience developing AI-enabled automation using LLMs.
- Experience with prompt engineering, agentic AI, tool or function calling, AI guardrails, and self-healing automation.
- Experience with one or more of LangChain, LangGraph, CrewAI, Semantic Kernel, AutoGen, or Model Context Protocol.
- Experience integrating enterprise applications with AI platforms such as OpenAI, Azure OpenAI, Claude, or Gemini.
- Experience using AI for automation, code generation, incident summarization, workflow orchestration, or knowledge retrieval.
- Experience with cloud and DevOps environments, Kubernetes, and enterprise integrations such as cloud SDKs or ServiceNow.
- Preferred experience with retrieval-augmented generation, vector databases, AI evaluation techniques, and knowledge graphs.
- Strong analytical, problem-solving, communication, collaboration, and continuous-learning skills.
Benefits
- Transparent compensation schemes and comprehensive location-tailored employee benefits supporting financial security, health, and wellbeing.
- Flexible working arrangements, advanced technology, and collaborative workspaces.
- Global orientation program and ongoing learning through Learning@MSCI, AI Learning Center, LinkedIn Learning Pro, and tailored development opportunities.
- Professional growth through multidirectional career paths, internal mobility, and expanded roles.
- Inclusive workplace culture with eight Employee Resource Groups and reasonable accommodation support.
Tech Stack
Categories
About MSCI Inc.
MSCI builds equity indexes, risk/portfolio analytics software, and ESG and climate datasets for institutional investors, who license benchmarks and subscribe to its research and tools. Its MSCI equity indexes are widely used as benchmarks for ETFs and institutional portfolios, and the firm also offers real estate and factor investing analytics. MSCI is headquartered in New York and is a public company listed on the NYSE (ticker: MSCI).