Solution Architect

As a seasoned AI / GenAI Solution Architect at our company, your role will involve designing, building, and delivering enterprise-grade GenAI platforms. You should have deep expertise in AI/ML, LLMs, and Agentic Frameworks, with strong technical acumen in Python, Azure AI stack, and CoPilot integrations. Your responsibilities will include: - Architecting and delivering end-to-end GenAI, LLM, and Agentic AI solutions for enterprise clients. - Designing scalable, secure, and cost-effective AI-ready architectures leveraging cloud technologies (Azure preferred). - Providing technical leadership in GenAI framework design, MLOps, and LLMOps implementations. - Developing AI CoPilots, chatbots, and agentic workflows using modern frameworks and APIs. - Leading proposal creation, estimations, and RFP/RFI responses for AI/GenAI engagements. - Collaborating with clients as a trusted AI advisor, driving solution roadmaps and transformation initiatives. - Building reference architectures, reusable components, and accelerators for GenAI adoption. - Collaborating cross-functionally with data engineering, product, and cloud teams to ensure successful delivery. Required Qualifications & Skills: - Experience: 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. In addition to the above, you will have hands-on Python, GenAI, LLM, and Agentic architecture experience, strong Azure and CoPilot expertise, and the ability to build (not just conceptualize) GenAI and agentic frameworks. You should also have a deep understanding of AI transformation programs at an enterprise scale.,