Generative AI Lead

Posted on August 8, 2025

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Job Description

  • *Job Title: Generative AI Lead*
  • *Location: (Noida ,Hyderabad ,Pune Bangalore Chennai ) Only in the first month, two visits to the client�s office in Noida Sector 144 are needed.)*
  • *Experience : 7 Years*
  • *Shift : IST*
  • About the Role:
  • We are seeking a highly skilled Generative AI Architect to lead the design, development, and deployment of cutting-edge GenAI solutions across enterprise-grade applications. This role requires deep expertise in LLMs, prompt engineering, and scalable AI system architecture, combined with hands-on experience in MLOps, cloud, and data engineering.
  • Key Responsibilities:
  • ? Design and implement scalable, secure GenAI solutions using large language models (LLMs) such as GPT, Claude, LLaMA, or Mistral.
  • ? Architect Retrieval-Augmented Generation (RAG) pipelines using tools like LangChain, LlamaIndex, Weaviate, FAISS, or ElasticSearch.
  • ? Lead prompt engineering and evaluation frameworks for accuracy, safety, and contextual relevance.
  • ? Collaborate with product, engineering, and data teams to integrate GenAI into existing applications and workflows.
  • ? Build reusable GenAI modules (function calling, summarization, Q&A bots, document chat, etc.).
  • ? Leverage cloud-native platforms (AWS Bedrock, Azure OpenAI, Vertex AI) to deploy and optimize GenAI workloads.
  • ? Ensure robust monitoring, logging, and observability across GenAI deployments (Grafana, OpenTelemetry, Prometheus).
  • ? Apply MLOps practices for CI/CD of AI pipelines, model versioning, validation, and rollback.
  • ? Research and prototype emerging trends in GenAI including multi-agent systems, autonomous agents, and fine-tuning.
  • ? Implement security best practices, data governance, and compliance protocols (PII masking, encryption, audit logs).
  • Required Skills & Experience:
  • ? 8+ years of overall experience in AI/ML, with at least 2�3 years focused on LLMs / GenAI.
  • ? Strong programming skills in Python, with frameworks like Transformers (Hugging Face), LangChain, or OpenAI SDKs.
  • ? Experience with Vector Databases (e.g., Pinecone, Weaviate, FAISS, Qdrant).
  • ? Proficiency in cloud platforms: AWS (SageMaker, Bedrock), Azure (OpenAI), GCP (Vertex AI).
  • ? Experience in designing and deploying RAG pipelines, summarization engines, and chat-based apps.
  • ? Familiarity with function calling, tool usage, agents, and LLM orchestration frameworks (LangGraph, AutoGen, CrewAI).
  • ? Understanding of MLOps tools: MLflow, Airflow, Docker, Kubernetes, FastAPI.
  • ? Exposure to prompt injection mitigation, hallucination control, and LLMOps.
  • ? Ability to evaluate GenAI systems using metrics like BERTScore, BLEU, GPTScore.
  • ? Strong communication and documentation skills; ability to lead architecture discussions and mentor engineering teams.
  • Preferred (Nice to Have):
  • ? Experience with fine-tuning open-source LLMs (LLaMA, Mistral, Falcon) using LoRA or QLoRA.
  • ? Knowledge of multi-modal AI (text-image, voice assistants).
  • ? Familiarity with domain-specific LLMs in Healthcare, BFSI, Legal, or EdTech.
  • ? Published work, patents, or open-source contributions in GenAI.

Required Skills

8+ years of overall experience in ai/ml with at least 2�3 years focused on llms / genai. ? strong programming skills in python with frameworks like transformers (hugging face) langchain or openai sdks. ? experience with vector databases (e.g. pinecone weaviate faiss qdrant). ? proficiency in cloud platforms: aws (sagemaker bedrock) azure (openai) gcp (vertex ai). ? experience in designing and deploying rag pipelines summarization engines and chat-based apps. ? familiarity with function calling tool usage agents and llm orchestration frameworks (langgraph autogen crewai). ? understanding of mlops tools: mlflow airflow docker kubernetes fastapi. ? exposure to prompt injection mitigation hallucination control and llmops. ? ability to evaluate genai systems using metrics like bertscore bleu gptscore. ? strong communication and documentation skills; ability to lead architecture discussions and mentor engineering teams. preferred (nice to have): ? experience with fine-tuning open-source llms (llama mistral falcon) using lora or qlora.