GenAI Solution Architect
3 weeks ago
About the RoleWe are seeking a seasoned AI / GenAI Solution Architect with deep expertise in AI/ML, LLMs, and Agentic Frameworks, who can design, build, and deliver enterprise-grade GenAI platforms. The ideal candidate will have strong technical acumen in Python, Azure AI stack, and CoPilot integrations, combined with hands-on experience in solution architecture, client engagement, and RFP/RFI leadership.Key ResponsibilitiesArchitect and deliver end-to-end GenAI, LLM, and Agentic AI solutions for enterprise clients.Design scalable, secure, and cost-effective AI-ready architectures leveraging cloud technologies (Azure preferred).Provide technical leadership in GenAI framework design, MLOps, and LLMOps implementations.Develop AI CoPilots, chatbots, and agentic workflows using modern frameworks and APIs.Lead proposal creation, estimations, and RFP/RFI responses for AI/GenAI engagements.Collaborate with clients as a trusted AI advisor, driving solution roadmaps and transformation initiatives.Build reference architectures, reusable components, and accelerators for GenAI adoption.Collaborate cross-functionally with data engineering, product, and cloud teams to ensure successful delivery.Required Qualifications & SkillsExperience:15+ years of overall IT experience, with 5+ years as an AI/ML/GenAI Architect.Technical Expertise:Strong hands-on expertise in Python for AI/ML development.Proven experience designing and implementing LLM and Agentic AI architectures.Deep understanding of GenAI frameworks, MLOps, and LLMOps.Strong exposure to data engineering pipelines (ETL, data lakes, orchestration).Hands-on with Azure AI stack (Azure OpenAI, Cognitive Services, CoPilot, AI Studio).Additional experience with GCP or AWS AI/ML services preferred.Familiarity with Databricks, Snowflake, Palantir, or similar data platforms.Client & Leadership Skills:Proven success in client-facing roles, handling RFPs, proposals, and estimations.Excellent stakeholder management, communication, and leadership abilities.Ability to mentor teams and build GenAI solution accelerators and PoCs.Preferred Certifications:Azure AI Engineer / Azure Solution Architect / GCP ML Engineer / AWS ML Specialist certifications are an advantage.Domain Exposure (Preferred):Experience in BFSI, Healthcare, Manufacturing, or Public Sector with regulatory-compliant AI systems.Key HighlightsHands-on Python, GenAI, LLM, and Agentic architecture experienceStrong Azure and CoPilot expertiseAbility to build (not just conceptualize) GenAI and agentic frameworksDeep understanding of AI transformation programs at enterprise scale
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