AI Engineer Team Lead

As an AI Engineer  Team Lead,  you will :

• Lead, mentor and professionally develop a team of AI engineers.

• Define the team’s technical roadmap, priorities, architecture and engineering standards   while remaining actively involved in architecture, research, design and development.

• Shape AI adoption across the company by building reusable AI capabilities, connecting organizational data and systems with models and agents and enabling R&D and product teams to develop AI-powered workflows and products.

• Manage model evaluation and benchmarking across quality, accuracy, latency, throughput, infrastructure requirements and cost.

• Be responsible for turning emerging AI technologies into practical, scalable and production-ready solutions.

• Identify and prioritize high-value AI use cases with development, product, research, and business teams.

• Lead AI initiatives from research and POC through architecture, development, deployment and production.

• Ensure strong engineering practices including testing, observability, Docker, CI/CD, GitOps, Kubernetes and Helm.

• Work closely with DevOps, infrastructure, research, development and product teams to deliver end-to-end AI solutions.

If you have :

• At least 2 years of management experience.

• Proven experience in designing reusable AI capabilities including RAG, GraphRAG, knowledge systems, agents, MCP/A2A integrations, tools and APIs.

• Experience in guiding model-serving and inference strategies using technologies such as vLLM, LiteLLM, SGLang, TGI or Triton.

• Ability to design systems that are reliable, scalable, secure, observable and cost-efficient.

• Strong hands-on software engineering and system design skills.

It would be great if you also have :

• A background in cybersecurity or security-data products.

• Experience building a new team or introducing AI practices across an engineering organization.