GEN AI Lead

2 days ago

Pune, Maharashtra, India Aikya Technologies Full time ₹ 12,00,000 - ₹ 36,00,000 per year

We are looking for an experienced GEN AI Lead / Architect with hands-on expertise in Generative AI and Agentic AI to design, develop, and deploy production-grade, enterprise-scale AI solutions. The ideal candidate should have strong proficiency in Python, Machine Learning, and multi-agent system orchestration, with proven experience delivering end-to-end implementations with minimal supervision.

Key Responsibilities :

Design, build, and orchestrate multi-agent systems capable of autonomous decision-making and task execution.

Lead the development and deployment of Generative AI solutions using LLMs and fine-tuned models.

Implement RAG (Retrieval-Augmented Generation) pipelines with robust document parsing, re-ranking, and context optimization.

Integrate AI agents into enterprise systems through APIs, function calling, and workflow orchestration frameworks (e.g., LangGraph, CrewAI, LlamaIndex, Haystack).

Fine-tune and evaluate LLMs (using LoRA, PEFT, or QLoRA) for domain-specific use cases.

Collaborate cross-functionally with data, platform, and DevOps teams to ensure scalable and secure AI deployments.

Ensure production-grade quality performance optimization, monitoring, and continuous improvement.

Provide technical mentorship to junior engineers (minimal team handling required).

Required Skills & Experience:

5 -10 years of total experience, with Min 3+ years in Generative AI and 1+ years Agentic AI with Min 2 or 3 Production grade implementation at Enterprise Level.

Strong background in Machine Learning, Deep Learning, and Python programming.

Hands-on experience with LLM frameworks (LangChain, LlamaIndex, Haystack, Semantic Kernel, etc.).

Proficiency in multi-agent orchestration (CrewAI, LangGraph, Swarm, Autogen, or custom frameworks).

Expertise in vector databases (FAISS, Pinecone, Chroma, Weaviate, etc.) and embedding models.

Proven fine-tuning experience using LoRA, QLoRA, or PEFT.

Experience in enterprise-grade GenAI & Agentic AI implementations — from PoC to production.

Strong understanding of RAG architecture, document chunking, context optimization, and model evaluation.

Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).

Excellent problem-solving and debugging skills.

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