Gen AI Implementation Lead/Architect

Overview

Lead the end-to-end implementation and adoption of Generative AI solutions across multiple client accounts, combining hands-on Azure or AWS AI engineering with client-facing and technical leadership.

What you'll do

• Lead end-to-end implementation of AI solutions across multiple client engagements.
• Design and deploy Generative AI solutions using Azure AI and/or AWS AI platforms.
• Build LLM-based applications, AI agents, Agentic workflows, and RAG solutions.
• Develop Python-based AI applications and integrate enterprise data, APIs, databases, and ITSM platforms.
• Implement prompt engineering, semantic search, vector databases, and AI security/governance best practices.
• Participate in client workshops, architecture discussions, PoCs, and production deployments.
• Address client queries related to AI architecture, security, governance, compliance, and deployment.
• Deliver AI training, documentation, and technical guidance to project teams and end users.

What you'll need

• Bachelor's or master's degree in computer science, AI, IT, or related field.
• 8–12 years of IT experience with 3–5 years in AI/Generative AI implementation.
• Hands-on experience delivering production-grade AI solutions on Azure and/or AWS.
• Strong knowledge of LLMs, Prompt Engineering, RAG, AI Agents, Agentic AI, Vector Databases, Semantic Search, and Responsible AI.
• Hands-on experience with Azure AI (Azure OpenAI, AI Foundry, AI Search) and/or AWS Bedrock, SageMaker.
• Strong programming skills in Python, REST APIs, and Git.
• Experience integrating AI with enterprise applications, databases, APIs, and ITSM tools (ServiceNow, Jira, BMC, Freshservice).
• Familiarity with AI developer tools such as GitHub Copilot, Claude, Cursor, Amazon Q, or Microsoft Copilot.

Nice to have

• Microsoft Certified: Azure AI Engineer Associate / Azure Solutions Architect.
• AWS Certified Machine Learning Engineer / AI Practitioner / AWS Solutions Architect.
• Generative AI or LLM certifications.

Details

• Job location: Hyderabad / Bangalore / Chennai / Kolkata / Noida / Gurgaon / Pune / Indore / Mumbai.
• Work model prioritizes in-person collaboration with flexibility to support wellbeing, productivity, individual work styles, and life circumstances.