Job Title: Lead AI Engineer (Agentic AI & Automation)  

Location – Remote – 2-11 PM  (Flexible in working hours)

Role Overview

We are seeking a visionary and hands-on Lead AI Engineer with over 8 years of experience to pioneer the development of next-generation Agentic AI systems and advanced automation workflows. In this role, you will bridge the gap between enterprise-grade cloud ecosystems and cutting-edge open-source AI frameworks.

You will lead the architecture, design, and implementation of autonomous AI agents capable of reasoning, planning, and executing complex tasks. The ideal candidate has deep expertise in the Microsoft Azure AI stack, Power Automate, and a strong command of open-source LLM orchestration frameworks. This is an outcome-driven role requiring strong technical leadership to transform complex business processes into highly automated, intelligent operations.

Key Responsibilities

1. Agentic AI Architecture & Development

Design, build, and deploy production-grade, autonomous AI agents and multi-agent systems that perform complex, goal-oriented tasks rather than simple conversational interactions.

Architect robust orchestration layers utilizing open-source frameworks (e.g., LangChain, LangGraph, MAF framework).

Implement advanced LLM techniques including Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and semantic caching.

2. Microsoft Azure & Power Automate Integration

Leverage the Microsoft Azure AI ecosystem (Azure OpenAI, Azure AI Search, Azure Machine Learning) to build secure, scalable AI backends.

Design and develop end-to-end enterprise automations by integrating AI agents with Power Automate (Desktop & Cloud flows), Power Apps, and custom API connectors.

Connect autonomous agents to enterprise data sources and legacy applications securely within cloud environments.

3. Technical Leadership & Strategy

Provide architectural governance and establish engineering best practices for code quality, testing, security, and MLOps/LLMOps pipelines.

Lead, mentor, and elevate a team of engineers, fostering a culture of continuous learning across both enterprise low-code and open-source pro-code stacks.

Collaborate with cross-functional stakeholders to evaluate business processes, identify AI opportunities, and define technical roadmaps with a focus on outcome-based delivery.

Required Technical Skills & Qualifications

Experience: 8+ years of professional experience in software engineering, data science, or AI/ML systems, with a proven track record in a technical leadership capacity.

AI & Agentic Frameworks: Hands-on experience building complex agentic workflows using open-source tools like LangChain, LangGraph, Microsoft Agent framework

Microsoft Ecosystem: Deep expertise in Azure OpenAI Service, Azure AI Search, and building enterprise-grade automations using Power Automate.

Programming & Core Stack: Advanced proficiency in Python and standard AI/ML libraries. Experience with API development using frameworks like FastAPI or Flask is highly desirable.

Data & Vector Databases: Strong experience working with Vector Databases (e.g., Pinecone, Milvus, Qdrant, or Azure AI Search) for semantic search and knowledge retrieval.

DevOps & LLMOps: Familiarity with deploying and monitoring LLMs in production, tracking agent trajectories, and managing CI/CD pipelines (Azure DevOps or GitHub Actions).

Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.

Preferred Soft Skills

Outcome-Oriented Mindset: Focused on delivering tangible business value and operational efficiency rather than just building technology for technology’s sake.

Exceptional Communication: Ability to articulate complex technical AI architectures to both highly technical engineering teams and non-technical business executives.

Problem-Solving Agility: A strong spark for experimentation, with the ability to navigate ambiguous requirements and rapidly prototype solutions using emerging open-source technologies.