About the Role
We 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 Responsibilities
- Architect 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 & 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.
Key Highlights
- Hands-on Python, GenAI, LLM, and Agentic architecture experience
- Strong Azure and CoPilot expertise
- Ability to build (not just conceptualize) GenAI and agentic frameworks
- Deep understanding of AI transformation programs at enterprise scale
