Description :

We are looking for an experienced Technical Lead AI / GenAI to drive the design, development, and delivery of advanced AI and Generative AI solutions within IT Operations Management (ITOM) and IT Service Management (ITSM) domains. This role combines deep hands-on technical expertise with architectural oversight and team leadership, ensuring that AI solutions are production-ready, scalable, secure, and aligned with enterprise standards.

The Technical Lead will act as a key technical decision-maker, mentor engineering teams, and collaborate closely with product owners, architects, and business stakeholders to deliver high-impact AI solutions.

Key Responsibilities :

Technical Leadership & Solution Ownership :

- Lead end-to-end design and implementation of AI/ML and Generative AI solutions from concept through production deployment.

- Provide technical direction, best practices, and architectural guidance to development teams.

- Review solution designs, code, and deployment pipelines to ensure quality, scalability, and maintainability.

AI / GenAI Development :

- Architect and develop solutions leveraging Large Language Models (LLMs) and NLP techniques.

- Build GenAI applications using frameworks such as LangChain, Hugging Face, OpenAI, and Azure OpenAI.

- Design and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.

- Apply Model Context Protocol (MCP) to manage contextual integrity, prompt lifecycle, and dynamic orchestration in GenAI systems.

Agentic AI & Intelligent Systems :

- Design and implement Agentic AI architectures that enable autonomous task execution, planning, reasoning, and orchestration.

- Lead the development of AI agents that interact with ITOM/ITSM tools, enterprise APIs, and operational workflows.

- Optimize agent collaboration patterns for complex, multi-step enterprise use cases.

Cloud, MLOps & Deployment :

- Lead deployment of AI solutions on AWS, Azure, or Google Cloud Platform (GCP).

- Implement and govern MLOps practices including CI/CD, model versioning, monitoring, retraining, and observability.

- Oversee containerized deployments using Docker and Kubernetes for scalable and resilient AI services.

Architecture & Integration :

- Design AI solutions aligned with SaaS-based architectures, microservices, and API-driven ecosystems.

- Ensure seamless integration of AI capabilities with existing enterprise systems and platforms.

- Collaborate with enterprise and solution architects to align with security, compliance, and governance standards.

Stakeholder Management & Communication :

- Translate business requirements into technical AI solutions and roadmaps.

- Communicate complex AI concepts, risks, and trade-offs clearly to technical and non-technical stakeholders.

- Partner with product, DevOps, and operations teams to ensure successful adoption and ongoing support.

Must-Have Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.

- Proven experience building and deploying AI/ML models in production, preferably within ITOM or ITSM environments.

- Strong hands-on expertise in :

1. LLMs, NLP, and Generative AI

2. LangChain, Hugging Face, OpenAI, Azure OpenAI

3. Working knowledge of:

4. Retrieval-Augmented Generation (RAG)

5. Model Context Protocol (MCP)

- Hands-on experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.

- Solid understanding of SaaS architectures, microservices, APIs, and containerization technologies (Docker, Kubernetes).

- Demonstrated leadership, communication, and mentoring capabilities.