Job Description

Role: AI Engineer- Tech Lead

We are looking for a highly skilled Tech Lead AI Engineer with a strong foundation in AI/ML technologies, hands-on engineering capabilities, and demonstrated leadership in managing and mentoring technical teams. The ideal candidate will bring 3-5 years of experience, including leading AI/ML projects or teams, working with intelligent agents, and building scalable, production-grade AI solutions using modern cloud infrastructure. This role requires balancing technical depth with strategic oversight, guiding team members, and driving innovation across projects. You will work across disciplines to solve real-world problems using cutting-edge AI, contributing to enterprise-grade intelligent systems that deliver measurable business value.

Key Responsibilities

1. AI Agent Development

Design and develop scalable multi-agent systems using Azure AI Foundry Agent Service and Semantic Kernel SDK. Build specialized agents (retrieval, planner, executor, evaluator) for end-to-end orchestration of complex workflows. Provide technical leadership in defining agent architectures, interface contracts, and scalability strategies.

2. Retrieval-Augmented Generation (RAG)

Implement text and multimodal RAG pipelines combining Azure AI Search, Cognitive Services, and Cosmos DB (Graph-RAG). Lead experimentation and optimization efforts to improve retrieval precision and grounding accuracy.

3. Model Management & LLMOps

Fine-tune, evaluate, and deploy LLMs (Azure OpenAI GPT?4o, GPT?3.5, Llama?2, Mistral) on Azure Machine Learning. Drive model lifecycle workflows using Prompt Flow, GitHub Actions, and CI/CD pipelines. Establish governance and review checkpoints for prompt, model, and agent deployments.

4. API & Integration Engineering

Expose agent capabilities via high-throughput REST and streaming WebSocket APIs using FastAPI or Azure Functions. Lead integration architecture with Microsoft 365 (Graph API, Teams, Power Platform) and third-party SaaS systems. Define API standards and security practices for internal and external integrations.

5. Trust, Safety & Observability

Implement safe, compliant operations using Azure AI content filters, RBAC, Application Insights, and telemetry dashboards. Define observability strategies and oversee incident tracking, alerting, and root cause analysis for agent behaviors.

6. Collaboration & Mentoring

Work closely with engineering, product, and UX teams in agile delivery cycles. Mentor junior and mid-level engineers in agentic design patterns, architecture decisions, and Azure-native development. Foster a culture of continuous learning through pair programming, code reviews, and internal knowledge sharing.

7. No-Code and Low-Code Approaches

Leverage platforms like Power Automate, Power Virtual Agents, and Builder.io to deliver AI solutions rapidly. Architect and validate no-code workflows for business teams while ensuring back-end integration integrity. Promote citizen development by supporting cross-functional stakeholders in low-code solution building.

8. Cross-Functional Leadership

Collaborate across disciplines to design, build, and deliver high-impact AI solutions with measurable outcomes. Translate complex technical concepts into business-friendly presentations for non-technical audiences. Balance technical contribution and team leadership, allocating time to unblock others and drive alignment.

9. Research, Upskilling, and R&D

Stay current with the latest advancements in AI, LLMs, RAG, and agentic architectures. Guide the team in tool evaluation, PoCs, and strategic technology adoption. Lead internal workshops, training sessions, and capability building initiatives.

Required Skills

Bachelor's degree in computer science, IT, or related field. 3-5 years of experience developing Agentic AI solutions; minimum 2 years in autonomous agent patterns. Proven experience leading AI teams or projects with clear business impact. Strong ability to mentor and upskill team members in both technical and architectural aspects. Expertise in designing scalable AI architectures and infrastructure for enterprise applications. Excellent communication skills for both technical stakeholders and non-technical leadership. Ability to balance hands-on technical work with strategic team leadership. Strong Python (preferred) or TypeScript; deep experience with FastAPI or Azure Functions. Deep knowledge of Microsoft Azure: Azure OpenAI, AI Search, AI Studio/Foundry, Cosmos DB, Container Apps, VNet networking. Hands-on with LangChain, Semantic Kernel, AutoGen, LangGraph or similar frameworks. Solid foundation in NLP, vector embeddings, and prompt engineering. Experience with vector and graph databases (Azure AI Search, Cosmos DB). Integration experience with Microsoft Graph API, REST APIs, and token-based authentication. GitHub/GitHub Actions or Azure DevOps for versioning and CI/CD. Strong analytical and troubleshooting skills; proven track record in solution design and stakeholder engagement.

Desired Skills

Exposure to multi?modal and graph?based RAG, function?calling, and tool former patterns. Experience deploying agents at scale with CI/CD and infrastructure?as?code. Familiarity with M365 Copilot Studio, Power Virtual Agents, and no?code/low?code AI builders. Teams Toolkit v5, Adaptive Cards, and M365 Copilot Studio. Experience with Web Sockets, SignalR for real?time agents. Certifications: DP?100, AI?900, Microsoft Certified: Azure AI Engineer Associate, or equivalent.

IMMEDIATE JOINERS

Job Type: Full-time

Benefits:

Health insurance Provident Fund
Work Location: In person