AI Engineering Lead - Agentic Engineering

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.

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

Mentor engineers on AI engineering, agentic architectures, software engineering practices, and AI-assisted development .

Stay current with rapidly evolving AI coding agents, agent frameworks, LLM capabilities, evaluation methodologies, and engineering practices.

Prototype emerging technologies and transition successful approaches into reliable production solutions.

Collaborate with clients and internal stakeholders to identify opportunities where Agentic AI can deliver measurable business and engineering value.

Context management → code generation → repository understanding → implementation → testing → debugging → code review → evaluation → iteration

Experience with MCP (Model Context Protocol) and building MCP servers/tools.

Experience with Claude, GPT, Gemini, Llama, or other frontier models .

Experience with AWS, Azure, or GCP .

Experience with Kubernetes, Docker, CI/CD, and cloud-native architectures .

Experience with LLM observability and tracing .

Experience with tools such as Langfuse, Arize Phoenix, OpenTelemetry, or similar .

Experience implementing automated agent evaluations, regression testing, and quality gates .

Experience with distributed systems and scalable AI inference.

Experience working in consulting/client-facing environments.

Build and scale production-grade Agentic AI systems , not just prototypes or chatbots.

Help Blend360 adopt Agentic Engineering across the SDLC .

Improve developer productivity through AI-assisted engineering workflows.

Establish repeatable approaches for context engineering, agent orchestration, tool use, and Evals .

Help teams safely adopt AI coding agents such as Claude Code, PI, Hermes Agent, and emerging equivalents .

Raise the engineering quality, reliability, and scalability of AI solutions delivered to clients.

Mentor engineers and become a technical authority in Agentic AI Engineering .