Gen AI - Team lead

GenAI / GenAI Architect TL/TM/SDM

Role & Responsibilities

• Design and develop Generative AI applications using Python for chatbots, summarization, intelligent automation and enterprise use cases.
• Develop and fine-tune LLMs and ML models for classification, prediction and decision support.
• Design and implement RAG solutions, embeddings, vector search and vector databases.
• Work with LangChain, Hugging Face, OpenAI and Pydantic for GenAI application development.
• Build and optimize prompts using zero-shot, few-shot and other prompt engineering techniques.
• Deploy and scale AI solutions using Azure OpenAI, Azure ML, Azure Functions, Cognitive Services, AWS SageMaker, Lambda and Bedrock.
• Integrate GenAI solutions with APIs, enterprise data platforms, Snowflake and business workflows.
• Design scalable AI/GenAI architecture and system solutions, including technology selection, deployment and model lifecycle management.
• Monitor and optimize model/system performance, scalability, reliability and cost.
• Ensure AI solutions follow appropriate security and compliance standards.
• Collaborate with Data Scientists, ML Engineers and business stakeholders to deliver production-ready GenAI solutions.

Required Skills

• 6–10 years of overall experience with 3+ years of relevant GenAI experience.
• Strong hands-on Python development.
• Strong experience with LLMs, RAG, embeddings and vector databases.
• Hands-on experience with LangChain, OpenAI and/or Hugging Face.
• Strong prompt engineering and LLM/model optimization knowledge.
• Experience with Azure / AWS / GCP, particularly GenAI model deployment.
• Knowledge of Machine Learning algorithms, training pipelines and model evaluation.
• Experience with FastAPI, Pydantic, Pandas and NumPy.
• Strong AI system design, architecture, scalability and enterprise integration experience.

Job Details

Location: Bengaluru / Hyderabad
Level: TL / TM / SDM
CTC: Up to 24 LPA
Notice Period: Immediate to 60 days
Interview Drive: Weekend Drive – 22nd August
Work Mode: Hybrid / as applicable