AI Lead Architect

The purpose of this role is to provide technical guidance and suggest improvements in development processes. Develop required software features, achieving timely delivery in compliance with the performance and quality standards of the company. Job Description:

Role Overview

• We are seeking an AI Tech Lead to engineer, scale, govern, and grow our AI delivery practice across GenAI, Agentic AI, and applied ML, within enterprise engagements. This is a strictly hands-on, individual contributor and technical leadership role. You will act as a core technical sentinel, helping grow frontier AI capabilities and engineering pillars. You will be expected to come with expertise that help you actively contribute towards directing technical capability growth for the AI practice. This role requires a builder’s mindset. You must possess deep technical fluency in Deep Learning architectures and agentic AI, built upon a rock-solid foundation of software engineering. You will lead technical execution, driving solution architectures, evaluation standards, and the technical bar for the AI engineering practice. The expectation is technical depth and breadth showcased across the portfolio of AI work done so far, preferably in multimodal agentic systems, SLM design, ML and DL solutions, and enterprise deployments, and enterprise platform deployments.

Key Responsibilities

Solution Engineering & Technical Execution

• Lead the hands-on engineering for end-to-end AI solutions across Deep Learning,GenAI, Agentic AI, and multimodal use cases.o Apply rigorous "fail fast" logic to all AI project management. Quickly identify,evaluate, and disqualify unviable AI use cases based on technical feasibility, effort,cost, and risk early in the cycle.o Perform explicit trade-off analysis on model class (frontier vs. SLM vs. fine-tuned),retrieval design, memory optimization, and orchestration. o Lead solutioning, support architecture for end-to-end AI solutions across GenAI,Agentic AI, multimodal, and applied ML use cases, with explicit trade-off analysison model class (frontier vs. SLM vs. fine-tuned), retrieval design, memory, andorchestration.o Own the practice's reference architectures and solution design patterns formultimodal agentic systems, including planning, tool use, memory, grounding, andinter-agent communication (MCP, A2A).o Conduct solution design reviews across concurrent client engagements; facilitatesubjective technical decisions and enable delivery excellence.