Lead AI Engineer - Agentic Engineering

We are looking for a Lead AI Engineer to help shape and build the next generation of Agentic AI and AI-powered engineering systems at Blend360 .

This is not a traditional GenAI or chatbot development role . We are looking for an experienced software/AI engineer who understands how to build production-grade agentic systems and, importantly, how to leverage Agentic Engineering as part of the Software Development Lifecycle (SDLC) .

You will work across AI engineering, software architecture, agent orchestration, LLM applications, developer productivity, and AI-assisted software development. You will help establish engineering practices around AI agents, context engineering, tool use, evaluations, autonomous task execution, and AI-augmented development workflows .

The ideal candidate combines strong software engineering fundamentals with hands-on experience building and operating real-world Agentic AI systems.
What You'll Do
Agentic Engineering & AI-Augmented SDLC

- Drive the adoption of Agentic Engineering practices across the software development lifecycle , using AI agents to augment and automate engineering workflows.

- Leverage tools and approaches such as Claude Code, Claude Code Skills, PI, Hermes Agent , and comparable AI coding/engineering agents as part of day-to-day software development.

- Build AI-assisted workflows covering requirements analysis, code generation, code understanding, refactoring, testing, debugging, documentation, code review, and deployment .

- Design agent workflows capable of understanding large codebases, managing context, using tools, executing multi-step engineering tasks, and recovering from failures.

- Establish best practices around context management, context engineering, tool calling, agent orchestration, guardrails, human-in-the-loop workflows, and autonomous task execution .

- Design and implement Evals to measure agent correctness, reliability, code quality, task completion, regression, and overall effectiveness.

- Continuously evaluate emerging agentic coding tools and techniques and identify opportunities to improve engineering productivity and software quality.

Production-Grade Agentic AI

- Architect and develop multi-agent and agentic systems capable of performing complex, multi-step tasks in production environments.

- Design agent architectures involving planning, reasoning, tool use, memory/context, execution, reflection, validation, and error recovery .

- Build agents that integrate with APIs, databases, enterprise systems, developer tools, and other external services.

- Develop reliable tool-use and MCP-based integrations where appropriate.

- Build production-grade LLM applications using frameworks such as LangGraph, LangChain, or equivalent orchestration frameworks .

- Implement RAG, semantic search, vector retrieval, structured outputs, and other LLM application patterns where required.

- Establish appropriate observability, evaluation, monitoring, security, and guardrails for agentic applications.

Software Engineering & Architecture

- Provide technical leadership across the design and development of AI-powered software products and platforms.

- Apply strong software engineering principles including system design, modular architecture, API design, scalability, reliability, testing, CI/CD, and maintainability .

- Build production-quality services and APIs using technologies such as Python, FastAPI, Docker, Kubernetes, and cloud platforms .

- Work closely with engineering, product, data, and client teams to translate complex business problems into scalable technical solutions.

- Conduct technical design reviews and provide mentorship to other AI/software engineers.

- Establish engineering standards and best practices for building AI and agentic applications.

Leadership & Innovation

- Act as a technical leader for Agentic AI initiatives and influence architecture and engineering decisions across teams.

- Mentor engineers on AI engineering, agentic ar