Hiring For Generative AI Lead/ Architect

Experience: 1020 Years
Location: PAN India
Employment Type: Full-Time

Role Overview

We are looking for an experienced Generative AI Lead / Architect to design, develop, and lead enterprise-grade Generative AI and Agentic AI solutions. The ideal candidate will have strong expertise in LLMs, RAG, AI agents, prompt engineering, cloud AI platforms, MLOps, and scalable AI architecture, along with the ability to lead technical teams and engage with business stakeholders.

Key Responsibilities

• Define and implement Generative AI architecture and technical strategy for enterprise use cases.
• Design scalable solutions using LLMs, RAG, vector databases, AI agents, and foundation models.
• Lead the development of AI applications using OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar platforms.
• Design and implement RAG pipelines, including document ingestion, chunking, embeddings, retrieval, reranking, and response generation.
• Develop Agentic AI solutions using tool calling, workflow orchestration, multi-agent architectures, and autonomous task execution.
• Evaluate and select appropriate LLMs based on accuracy, latency, cost, security, and business requirements.
• Establish standards for prompt engineering, model evaluation, hallucination reduction, guardrails, and responsible AI.
• Integrate Generative AI solutions with enterprise applications, APIs, databases, and cloud platforms.
• Define MLOps/LLMOps practices for model deployment, monitoring, versioning, evaluation, and continuous improvement.
• Lead proof-of-concepts and convert successful prototypes into production-ready enterprise solutions.
• Mentor AI/ML engineers, developers, and architects and provide technical leadership.
• Collaborate with business, product, security, data, and engineering teams to translate business problems into AI solutions.
• Drive technical reviews, architecture discussions, design documentation, and implementation standards.
• Ensure solutions meet requirements for security, privacy, scalability, performance, and compliance.

Mandatory Technical Skills

• 10–20 years of experience in AI/ML, Data Science, Software Engineering, or Architecture.
• Strong hands-on experience with Generative AI and Large Language Models (LLMs).
• Expertise in Python and AI/ML frameworks.

• Strong understanding of:

• RAG
• Prompt Engineering
• Embeddings
• Vector Databases
• Fine-tuning
• LLM evaluation
• AI Agents / Agentic AI
• Function/Tool Calling

• Guardrails

• Experience with LLM platforms such as Azure OpenAI, OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, or open-source LLMs.
• Experience with vector stores such as Pinecone, FAISS, Milvus, Weaviate, Elasticsearch/OpenSearch, or Azure AI Search.
• Experience with frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, or equivalent.
• Strong knowledge of REST APIs, microservices, cloud architecture, and distributed systems.
• Experience with AWS / Azure / GCP and cloud-native AI services.
• Knowledge of Docker, Kubernetes, CI/CD, MLOps/LLMOps, and model deployment.
• Strong understanding of AI security, data privacy, responsible AI, and enterprise governance.

Preferred Skills

• Experience with Agentic AI and multi-agent systems.
• Experience implementing enterprise Copilot / Virtual Assistant / AI Assistant solutions.
• Knowledge of Knowledge Graphs, Graph RAG, multimodal AI, speech AI, and computer vision.
• Experience with model fine-tuning, LoRA/QLoRA, and open-source models such as Llama, Mistral, or similar.
• Experience with AI observability and evaluation platforms.
• Understanding of NLP, deep learning, transformers, and machine learning algorithms.
• Experience working with large-scale enterprise data platforms.