Gen AI Implementation Lead/Architect

• 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.

• 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.

• 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.

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

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