Solution Architect

About the Role:

We are looking for a Tech Lead - AI Agentic Systems to lead the design and delivery of next-generation AI applications and platforms. The ideal candidate will be an experienced hands-on technologist and mentor, with a deep understanding of Generative AI, Agentic AI, Databricks, MLOps, and cloud-native architecture. This role combines strategic technical leadership, hands-on development, and team enablement to build scalable, intelligent systems from LLM-powered solutions to multi-agent ecosystems that integrate seamlessly with enterprise systems.

Key Responsibilities

Technical Leadership

• Lead a team of AI engineers and data scientists to architect, develop, and deploy intelligent AI systems.
• Drive end-to-end design of LLM-based, multi-agent, and autonomous AI frameworks, ensuring scalability, governance, and security.
• Mentor junior engineers, conduct code reviews, and enforce engineering best practices.
• Partner with product, data, and cloud teams to align technical delivery with business outcomes.

Architecture Solution Design

• Define architectural blueprints for RAG pipelines, MCP-based agentic systems, and AI integration layers.
• Lead implementation of Databricks Lakehouse-based MLOps pipelines using MLflow, Delta Lake, and Feature Store.
• Architect high-availability AI workloads across AWS / Azure / GCP environments.

Innovation Implementation

• Build and orchestrate AI agents using LangChain, CrewAI, AutoGen, LangGraph, or Semantic Kernel.
• Establish frameworks for tool invocation, agent collaboration, and Model Context Protocol (MCP) communication.
• Drive experimentation with new AI techniques multi-modal models, autonomous planning, or symbolic reasoning.

Governance Quality

• Implement best practices for Responsible AI, observability, and model explainability.
• Define AI evaluation frameworks, safety protocols, and quality assurance mechanisms for LLMs and agents.
• Ensure compliance with organizational and cloud governance policies.