Agentic/Gen AI Practice Head, Hyderabad

Key Responsibilities :

• AI Product Development:
  Design and develop scalable AI-driven products, from proof of concept (POC) to production-ready systems.
• Generative AI Engineering:
  Fine-tune, prompt-engineer, and deploy LLMs (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.) for text, chat, code, and multimodal use cases.
• Agentic AI Systems:
  Build multi-agent architectures that autonomously reason, plan, and execute tasks across enterprise workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.
• End-to-End Implementation:
  Develop and orchestrate intelligent pipelines integrating AI models, vector databases (FAISS, Pinecone, Chroma), APIs, and orchestration tools (n8n, Airflow, Azure AI Studio, etc.).
• Data Integration:
  Work with structured and unstructured data sources, performing embedding generation, RAG optimization, and semantic search implementation.
• Productization:
  Transform AI prototypes into production-ready applications using MLOps best practices and cloud-native deployment (Azure, AWS, GCP).
• Cross-Functional Collaboration:
  Work closely with business analysts, product owners, and solution architects to identify automation and decision-making opportunities via Agentic AI.
• Continuous Innovation:
  Research and implement emerging frameworks in autonomous agents, tool use, memory-based reasoning, and multi-modal integration.

Required Skills :

• Core AI Expertise:
• LLMs (GPT-4, Claude, Gemini, Llama, Mistral, etc.)
• Generative AI frameworks (LangChain, LlamaIndex, Semantic Kernel, CrewAI)
• Vector databases (FAISS, Pinecone, Milvus, Weaviate, Chroma)
• Knowledge of RAG, prompt engineering, and few-shot learning
• Agentic AI Proficiency:
• Experience in multi-agent orchestration and memory frameworks
• Workflow design with planningactingreflection loops
• Integration with APIs, databases, and third-party systems
• Programming Skills:
• Python (FastAPI, Flask), JavaScript/TypeScript (Node.js), or similar
• Familiarity with libraries like Transformers, OpenAI API, LangChain, and Pydantic
• Cloud & Deployment:
• Experience with Azure AI Studio, AWS Bedrock, or GCP Vertex AI
• Containerization (Docker), CI/CD, and MLOps pipelines
• Data Engineering Understanding:
• Familiar with ETL, data cleaning, and embedding generation pipelines
• Soft Skills:
• Strong problem-solving, innovation mindset, and communication skills
• Ability to collaborate in agile, cross-functional environments

If you meet the above criteria and are interested in this opportunity, please share your updated resume at hema@tekleaders.com or feel free to reach out for more details.