Manager- Artificial Intelligence
ReNew
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Descrizione del lavoro
ReNew is seeking a Manager- Artificial Intelligence in Gurugram to lead AI strategy, architecture, and delivery across business units. You will guide GenAI initiatives, oversee end-to-end solution development, and mentor data scientists and AI engineers while ensuring governance and robust observability.
The role requires 6-8 years in DS/ML/AI, strong production experience, and ownership of AI/GenAI projects, with leadership responsibilities across cross-functional teams and stakeholders.
Competenze
- 6-8 years across Data Science, ML and AI Engineering.
- Strong DS/ML foundation with progression into production AI Engineering.
- Significant technical ownership of 1-2+ production AI/GenAI solutions.
- Experience leading AI architecture and technical teams.
Mansioni
- Identify and prioritise AI, GenAI, analytics opportunities across business functions.
- Translate business problems into 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.
Conoscenze
Formazione
Strumenti
Descrizione del lavoro
Job Description:
Working @ Renew
Working here means you’ll be part of something genuinely special . Funded by marquee investors and guided by a unique set of values, ReNew is the leading renewable energy IPP in India in terms of total energy generation capacity. We take pride in providing opportunities to our employees to create, explore, express, take risks and grow. As a ReNewer, you’ll always be doing things that would be beneficial to millions.
- 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.
- 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.
- 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.
- 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.
- 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.
- Strong 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.
- 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
DS/ML to AI Engineering to Production GenAI to Agentic Architecture to Technical Leadership
- 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.
- Strong 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.
- 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
DS/ML to AI Engineering to Production GenAI to Agentic Architecture to Technical Leadership
Requirements:
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