GenAI Solution Architect

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