Lead Architect – AI & Agentic Engineering

Project overview

This is a hands-on Lead Architect role focused on exploring, prototyping, and scaling GenAI and agentic capabilities for AI-native products and engineering accelerators across DPS. The core requirements are practical experience building GenAI and agentic applications, strong knowledge of LLM application patterns and agent frameworks, Python and backend engineering, cloud-native architecture, and production engineering practices.

The role also calls for defining architecture and engineering practices for orchestration, evaluation, security, governance, and observability; AI coding tools and AI-powered SDLC experience are preferred. The structured experience range is 6–12 years, and the employment type is contract. The stated locations are Gurugram and Pune; work mode is not specified, and the description does not identify a specific industry or product vertical.

Responsibilities

• Explore emerging AI technologies, agentic frameworks, tools, and architectural patterns.
• Identify opportunities across AI-native applications, autonomous workflows, and AI-first software development.
• Develop technical POVs, reference architectures, and recommendations backed by hands-on experimentation.
• Personally design and develop agentic POCs, prototypes, and compelling demonstrations.
• Build reusable agents, skills, tools, and engineering accelerators for adoption across DPS.
• Experiment with AI-powered SDLC, including development, testing, and modernization.
• Translate successful prototypes into production-ready capabilities.
• Define architecture patterns for AI-native and agent-enabled digital products.
• Explore new experiences designed for both human users and AI agents.
• Establish best practices for orchestration, context engineering, evaluation, observability, security, and governance.
• Convert innovations into differentiated offerings, reusable assets, and client opportunities.
• Present technical POVs and demonstrations in internal and external forums.

Requirements

• Hands-on development of GenAI and agentic applications
• LLM application patterns, including RAG, tool calling, agent orchestration, context engineering, and multi-agent systems
• Experience with agent frameworks such as LangGraph, Semantic Kernel, OpenAI Agents SDK, or equivalent
• Knowledge of MCP, agent interoperability, evaluation, guardrails, and human-in-the-loop workflows
• Strong Python programming and modern backend engineering
• Experience with APIs, microservices, cloud-native architectures, and full-stack product engineering
• Experience with AWS, Azure, or GCP and associated AI services
• Understanding of DevOps, CI/CD, security, testing, and production engineering
• Ability to define AI-native and agent-enabled product architecture, including orchestration, observability, and governance

Project details

• Start: flexible
• Remote: hybrid
• Location: India, IN
• Languages: English