Lead AI Engineer - Agentic Engineering

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com .

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.

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,