AI/ML Lead

AI Technical Lead (LLM & Agentic AI)

About the Role

Job Title: AI Technical Lead (LLM & Agentic AI)
Client Sector / Domain Preference: AI / Digital Transformation / Enterprise Technology
Working Model: On-site 
Role Type: Permanent

Role Overview

We are looking for an experienced AI Technical Lead to lead the build-and-deploy activities for enterprise-scale AI solutions. This role serves as the primary technical counterpart to external architecture partners, ensuring that AI solutions are implemented with high engineering standards, scalability, security, and operational excellence.

The primary purpose of this role is to translate architecture designs into high-quality production systems while leading a team of engineers through the development, testing, deployment, and operationalization of AI applications. The successful candidate will remain hands-on, building critical components while guiding engineering teams and driving delivery excellence.

The role requires strong expertise in Large Language Models (LLMs), Agentic AI systems, Retrieval Augmented Generation (RAG), MLOps, software engineering best practices, and cloud-native AI platforms.

Key Responsibilities

1. Lead the build-and-deploy effort for AI and GenAI solutions, ensuring adherence to established architecture, engineering standards, and delivery timelines.
2. Act as the technical counterpart to solution architects and technology partners, reviewing and challenging solution designs where necessary.
3. Drive implementation of production-grade LLM and Agentic AI applications.
4. Own overall code quality, testing strategy, evaluation frameworks, and deployment governance.
5. Develop reusable frameworks, reference implementations, and core platform components.
6. Guide engineering teams in building scalable, secure, and maintainable AI solutions.
7. Establish CI/CD pipelines, MLOps practices, and deployment automation processes.
8. Manage code reviews, design reviews, and engineering quality assurance activities.
9. Identify technical risks, dependencies, and delivery challenges, and proactively drive mitigation plans.
10. Collaborate closely with business stakeholders, architects, product teams, and engineering leadership.
11. Mentor engineering teams and support knowledge transfer for long-term solution ownership.
12. Ensure compliance with enterprise security, governance, and responsible AI practices.

Required Skills & Experience

1. 8–10 years of experience in Software Engineering, AI Engineering, or Machine Learning Platform Development.
2. Strong hands-on programming expertise in:
   • Python (Preferred)
   • C# / .NET
   • TypeScript
3. Proven experience building and deploying production-grade LLM applications.
4. Hands-on expertise with:
   • Agentic AI Systems
   • Multi-Agent Architectures
   • Retrieval Augmented Generation (RAG)
   • Tool Calling / Function Calling
   • AI Orchestration Frameworks
5. Strong understanding of prompt engineering, evaluation frameworks, and AI application optimization.
6. Experience designing and implementing scalable AI services and APIs.
7. Strong software engineering fundamentals including:
   • Object-Oriented Design
   • Design Patterns
   • Secure Coding Practices
   • Version Control
8. Proven experience establishing CI/CD and MLOps practices.
9. Strong expertise in testing frameworks, code quality standards, and production deployment.
10. Experience leading engineering teams and driving technical delivery.
11. Ability to analyze, challenge, and implement complex architectural designs.
12. Strong stakeholder communication and technical leadership capabilities.

Desirable Skills & Experience

1. Experience with Azure AI Foundry and Azure OpenAI Services.
2. Hands-on experience with:
   • LangChain
   • LangGraph
   • Semantic Kernel
   • AutoGen
3. Experience implementing enterprise-grade AI governance and responsible AI controls.
4. Knowledge of vector databases and semantic search technologies.
5. Experience with Kubernetes, Docker, and cloud-native deployment patterns.
6. Experience delivering solutions within partner-led or vendor-led architecture environments.
7. Exposure to Manufacturing, Compliance, Risk, or Enterprise Operations domains.
8. Experience enabling customer teams through mentoring and knowledge transfer initiatives.
9. Familiarity with enterprise integration platforms and API ecosystems.

Technical Competencies

AI & Generative AI

• Large Language Models (LLMs)
• Agentic AI Systems
• RAG Architecture
• Prompt Engineering
• AI Evaluation Frameworks
• Tool & Function Calling
• Multi-Agent Workflows

Cloud & AI Platforms

• Azure OpenAI
• Azure AI Foundry
• Azure AI Services
• Cloud-Native AI Deployments

Engineering & DevOps

• Python
• C#/.NET
• TypeScript
• Git
• CI/CD Pipelines
• Automated Testing
• MLOps
• Containerization

Frameworks

• LangChain
• LangGraph
• Semantic Kernel
• AutoGen

Conclusion – Ideal Candidate Profile

The ideal candidate will be a highly skilled AI Technical Lead with extensive experience building production-grade LLM and Agentic AI solutions. They should possess strong software engineering fundamentals, hands-on development expertise, and the ability to lead engineering teams while remaining actively involved in implementation activities.

The successful candidate will demonstrate a balance of technical depth, leadership capability, architectural thinking, and delivery excellence. They should be comfortable engaging with external architects, challenging technical decisions, and ensuring the development team delivers robust, scalable, and maintainable AI solutions.

Candidates with Azure AI expertise, strong MLOps experience, and a track record of delivering enterprise AI applications will be highly regarded.

Additional Requirements

• Notice Period: Immediate Joiners Preferred
• Leadership Requirement: Team Management & Technical Mentoring
• Core Skills: LLMs, Agentic AI, RAG, Python, Azure OpenAI, MLOps, LangChain, Software Architecture, CI/CD, Production Deployment