Generative AI Lead / Architect

Role Overview

We seek a seasoned Generative AI Lead / Architect to architect and steer enterprise-grade Generative AI and Agentic AI initiatives. This leadership role involves designing scalable AI solutions leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI agents, prompt engineering, and cloud AI platforms. The candidate should be adept at guiding technical teams and collaborating closely with business stakeholders.

Key Responsibilities

• Develop and execute the Generative AI architectural framework and technical strategies tailored for enterprise applications.
• Create scalable AI implementations using LLMs, RAG, vector databases, AI agents, and foundational AI models.
• Lead the development of AI applications on platforms such as OpenAI, Azure OpenAI, AWS Bedrock, and Google Vertex AI.
• Architect and operationalize RAG pipelines involving document ingestion, chunking, vector embeddings, retrieval, reranking, and response generation.
• Construct Agentic AI solutions utilizing tool invocation, workflow orchestration, multi-agent frameworks, and autonomous task execution methodologies.
• Assess and select LLMs considering factors like accuracy, latency, cost, security, and business needs.
• Establish enterprise-wide standards for prompt engineering, model assessment, hallucination mitigation, guardrails, and ethical AI practices.
• Integrate Generative AI solutions seamlessly with enterprise applications, APIs, databases, and cloud infrastructures.
• Define and uphold MLOps/LLMOps processes encompassing model deployment, monitoring, version control, evaluation, and iterative enhancement.
• Lead proof-of-concept initiatives and transition successful prototypes to production-grade solutions.
• Mentor AI/ML engineers, developers, and architects, offering strong technical guidance.
• Collaborate with cross-functional teams including business, product, security, data, and engineering to translate business challenges into AI-driven solutions.
• Oversee technical reviews, architectural discussions, documentation, and implementation standards.
• Ensure all solutions comply with security, privacy, scalability, performance, and regulatory standards.

Required Qualifications and Skills

• Experience spanning 10 to 20 years in AI/ML, Data Science, Software Engineering, or technical Architecture.
• Extensive hands-on expertise in Generative AI and Large Language Models (LLMs).
• Proficiency in Python programming along with relevant AI/ML frameworks.
• In-depth knowledge of Retrieval Augmented Generation (RAG), prompt engineering, embeddings, vector databases, fine-tuning techniques, LLM evaluation, AI Agents, tool calling, and guardrails.
• Familiarity with LLM platforms such as Azure OpenAI, OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, and open-source LLMs.
• Experience with vector data stores like Pinecone, FAISS, Milvus, Weaviate, Elasticsearch/OpenSearch, or Azure AI Search.
• Hands-on with frameworks including LangChain, LlamaIndex, Semantic Kernel, LangGraph, or similar technologies.
• Sound understanding of REST APIs, microservices architectures, cloud technologies, and distributed systems.
• Knowledge and experience using AWS, Azure, or Google Cloud Platform and their cloud-native AI services.
• Experience with containerization technologies Docker and Kubernetes, CI/CD pipelines, MLOps/LLMOps methodologies, and managing model deployments.
• Strong awareness of AI security practices, data privacy protocols, responsible AI principles, and enterprise governance.

Preferred Additional Skills

• Experience with Agentic AI structures and multi-agent systems.
• Background in implementing enterprise AI solutions such as Copilot, Virtual Assistants, or AI Assistants.
• Exposure to Knowledge Graphs, Graph-based RAG, multimodal AI, speech AI, and computer vision technologies.
• Experience in model fine-tuning approaches including LoRA/QLoRA and working with open-source models like Llama or Mistral.
• Familiarity with AI observability tools and platforms for evaluation purposes.
• Understanding of NLP, deep learning models, transformers, and various machine learning algorithms.
• Experience managing large-scale enterprise data platforms.

Additional Details

• Work Location: Hyderabad, India (PAN India applicable).
• Employment Status: Full-time.
• Educational Eligibility: Open to candidates holding any graduate degree.
• Experience Range: 10 to 20 years professional experience.
• Annual Salary Range: INR 2,500,000 to 4,000,000.