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 efficient, 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- Manager- Artificial intelligence

Experience- 5-7 years

Location- Gurgoan

Key Responsibilities

AI & Digital Transformation

- Identify and prioritise AI, GenAI, analytics and agentic AI opportunities across business functions.
- Translate business problems into appropriate AI/ML, GenAI, RAG or automation solutions.
- Drive enterprise AI solutions including assistants, copilots, analytical agents and multi-agent workflows.
- Evaluate emerging AI technologies and recommend solutions aligned with business objectives.

Solution Architecture & Delivery

- Lead end-to-end delivery of AI solutions from ideation and architecture to production deployment.
- Architect scalable RAG, GraphRAG and multi-agent solutions using LangGraph/LangChain.
- Design reusable agents, tools and AI services that can be independently deployed and integrated.
- Lead development of secure and scalable Python/FastAPI services.
- Define engineering standards for APIs, agent contracts, authentication, rate limiting, error handling and deployment.
- Establish production practices covering CI/CD, testing, evaluation, monitoring and support.

Stakeholder & Technical Leadership





- Partner with business, Data Science, Cloud, Cybersecurity and Engineering teams.
- Act as a trusted technical advisor on AI strategy, architecture and implementation.
- Mentor Data Scientists and AI Engineers and conduct architecture/code reviews.
- Communicate solution progress, risks, business impact and ROI to leadership.

AI Governance & Observability

- Ensure secure and responsible deployment of AI solutions.
- Establish practices for access control, data security, grounding, AI governance and human oversight.
- Establish LLM/agent tracing and observability using Langfuse or equivalent tools.
- Define evaluation frameworks for retrieval quality, answer quality, latency, cost and business effectiveness.

Required Qualifications
- Bachelor's degree in Engineering, Computer Science, Data Science, AI or related field. Master's preferred.
- 6-8 years across Data Science, ML and AI Engineering.
- Robust DS/ML foundation with demonstrated progression into production AI Engineering.
- Significant technical ownership of 1-2+ production AI/GenAI solutions.
- Experience leading AI architecture and technical teams.

Technical Expertise
- Python, FastAPI and REST APIs
- GenAI, LLMs, RAG and GraphRAG
- LangGraph / LangChain
- Agentic and multi-agent architecture
- Langfuse / LLM observability
- Azure / Azure OpenAI
- Docker, CI/CD and Kubernetes/AKS exposure
- API security, authentication and rate limiting
- Vector databases, Redis and Knowledge Graphs/Neo4j
- AWS exposure is an advantage

Preferred Profile Trajectory: DS/ML AI Engineering Production GenAI Agentic Architecture Technical Leadership

📌 Manager- Artificial intelligence (Haryana)
🏢 RENEW
📍 Haryana