Data & AI Solutions Lead – AI & Analytics

About the role

We are looking for a Data & AI Solutions Lead to drive the design, delivery and continuous improvement of LLM‑based and agentic AI solutions for our clients and internal business units. The role combines strategic opportunity identification, solution architecture, team leadership and hands‑on technical delivery in a hybrid work environment.

Key responsibilities

• Identify and propose new data analytics and AI opportunities, develop business cases and lead scoping workshops with clients.
• Design custom AI solutions—including multi‑agent pipelines, Retrieval‑Augmented Generation (RAG) systems and LLM‑powered workflows—selecting appropriate tools, frameworks and models.
• Own end‑to‑end deployment in client and cloud environments, managing CI/CD pipelines, containerization, monitoring and post‑deployment performance.
• Define quality metrics, build evaluation loops for LLM and agent outputs, and drive continuous enhancement based on user feedback.
• Stay current on emerging LLM, agentic and MLOps/LLMOps technologies, evaluate their fit and champion technical standards across the organization.
• Lead and mentor a growing team of AI engineers, data scientists and analysts, handling performance management, hiring and career development.

Required profile

• 6+ years of experience delivering data analytics, data science or AI solutions, with a proven track record of end‑to‑end ownership.
• Demonstrated ability to work with both business stakeholders and technical teams, translating business needs into concrete technical proposals.
• Experience managing client‑facing projects, including proposal writing, RFP/RFI responses and contract negotiations.
• Strong leadership skills with experience building, coaching and scaling technical teams.

Required skills

• LLM‑based systems and agentic frameworks
• MLOps / LLMOps pipelines
• CI/CD, Docker and containerization
• Cloud environment configuration and monitoring
• Data analytics and data science methodologies
• Retrieval‑Augmented Generation (RAG) architectures