About Company

Founded in 2011, ReNew, is one of the largest renewable energy companies globally, with a leadership position in India. Listed on Nasdaq under the ticker RNW, ReNew develops, builds, owns, and operates utility-scale wind energy projects, utility-scale solar energy projects, utility-scale firm power projects, and distributed solar energy projects. In addition to being a major independent power producer in India, ReNew is evolving to become an end-to-end decarbonization partner providing solutions in a just and inclusive manner in the areas of clean energy, green hydrogen, value-added energy offerings through digitalisation, storage, and carbon markets that increasingly are integral to addressing climate change. With a total capacity of more than 13.4 GW (including projects in pipeline), ReNew’s solar and wind energy projects are spread across 150+ sites, with a presence spanning 18 states in India, contributing to 1.9 % of India’s power capacity. Consequently, this has helped to avoid 0.5% of India’s total carbon emissions and 1.1% India’s total power sector emissions. In the over 10 years of its operation, ReNew has generated almost 1.3 lakh jobs, directly and indirectly. ReNew has achieved market leadership in the Indian renewable energy industry against the backdrop of the Government of India’s policies to promote growth of this sector. ReNew’s current group of stockholders contains several marquee investors including CPP Investments, Abu Dhabi Investment Authority, Goldman Sachs, GEF SACEF and JERA. Its mission is to play a pivotal role in meeting India’s growing energy needs in an effective, sustainable, and socially responsible manner.



ReNew stands committed to providing clean, safe, affordable, and sustainable energy for all and has been at the forefront of leading climate action in India.

Job Description

Role- Deputy Manager- Artificial intelligence

Experience: 4-5 years

Location- Gurgoan

Key Responsibilities

AI & Digital Transformation

- Identify AI, GenAI, ML, analytics and automation opportunities across business functions.
- Translate business requirements into appropriate ML, GenAI, RAG or agentic AI solutions.
- Develop enterprise assistants, analytical agents and intelligent AI applications.
- Evaluate emerging AI models, frameworks and technologies.

Solution Delivery & AI Engineering

- Independently own AI solutions from problem definition through production deployment.
- Design and build RAG, conversational AI and agentic workflows.
- Develop multi-step workflows using LangGraph/LangChain.
- Build production-grade Python and FastAPI services.
- Integrate AI agents with APIs, databases, analytical models and enterprise systems.
- Implement authentication, validation, error handling, rate limiting, retries and timeouts.
- Containerise and deploy AI services using Docker and Azure.
- Develop reusable AI capabilities rather than use-case-specific applications.





Stakeholder Management

- Work with business teams to understand problems, outcomes and success metrics.
- Partner with Data Science, Cloud, Cybersecurity and Engineering teams to productionise AI solutions.
- Communicate solution design, progress, dependencies and technical risks.
- Mentor junior AI Engineers and participate in technical/code reviews.

AI Governance & Observability

- Ensure secure and responsible deployment of AI solutions.
- Implement controls for data access, secrets, grounding and unauthorised agent/tool usage.
- Implement LLM and agent tracing using Langfuse or equivalent platforms.
- Evaluate retrieval quality, answer quality, tool selection, latency and errors.

Required Qualifications
- Bachelor's degree in Engineering, Computer Science, Data Science, AI or related field. Master's preferred.
- 4-5 years across Data Science, ML and AI Engineering.
- Strong DS/ML foundation with demonstrated transition into production AI Engineering.
- Hands-on contribution to 1-2 production or production-scale AI/GenAI solutions.
- Ability to independently own an AI solution or major technical component.

Technical Expertise
- Data Science and ML fundamentals
- Python and FastAPI
- GenAI, LLMs and RAG
- LangGraph / LangChain
- AI agents and tool calling
- Langfuse / LLM observability
- Azure / Azure OpenAI
- Docker and CI/CD
- API security and authentication
- Redis and vector databases
- Neo4j / GraphRAG exposure
- AWS exposure is an advantage

Preferred Trajectory: DS/ML GenAI Production AI Engineering End-to-End Solution Ownership.

📌 Deputy Manager- Artificial Intelligence (Haryana)
🏢 RENEW
📍 Haryana