GenAI / LLM Engineer | RAG | Agentic AI | Python | Multi-Agent Systems
Experience
6 – 12 Years
Location
Pune (Hybrid)
Notice Period
(Immediate Joiners or March notice serving candidates)
Job Summary
We are looking for a skilled Generative AI Engineer with hands-on experience in LLMs, RAG pipelines, and Agentic AI systems. The ideal candidate will design and build intelligent, scalable AI solutions using up-to-date frameworks and multi-agent architectures.
Key Skills Required
- Generative AI / GenAI
- Large Language Models (LLMs)
- RAG (Retrieval-Augmented Generation)
- Python Programming
- Agentic AI / AI Agents
- Multi-Agent Systems
Tools & Frameworks
- LangChain / LlamaIndex
- Vector Databases: Pinecone, Weaviate, FAISS
- LLM APIs: OpenAI, Anthropic
- Hugging Face Transformers
- Prompt Engineering & Fine-tuning techniques
Key Responsibilities
- Design and implement LLM-powered applications using GenAI frameworks
- Build and optimize RAG pipelines for enterprise use cases
- Develop Agentic AI systems and multi-agent workflows
- Integrate LLMs with external data sources and APIs
- Develop scalable backend services using Python
- Work with vector databases and semantic search systems
- Perform prompt engineering, evaluation, and tuning of AI models
- Collaborate with cross-functional teams to deliver AI-driven solutions
Preferred Experience
- Experience in building AI Agents / Autonomous Systems
- Strong understanding of NLP and Machine Learning concepts
- Hands-on with real-time AI applications / chatbots / copilots
- Exposure to cloud platforms (Azure / AWS / GCP)
- Knowledge of MLOps / LLMOps practices
Soft Skills
- Strong problem-solving and analytical thinking
- Excellent communication skills
- Ability to work in a fast-paced, innovation-driven environment
Additional Info
- Opportunity to work on cutting-edge GenAI projects
- Exposure to enterprise-scale AI transformations
- Collaborative and innovation-focused work culture
How to Apply
Interested candidates can share their updated resume with relevant project details in GenAI / LLM / RAG / Agentic AI
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