If you are an AI builder who thrives on taking ideas from vision to whiteboard (or demo) to production - and enjoys collaborating within a larger team to shape the future of enterprise AI - this role is for you. We are looking for Managers within our Data & AI Consulting Practice to own the full AI lifecycle: shaping end-to-end solutions during pre-sales, leading enterprise ML/GenAI programs into production, and working on building scalable, market-ready AI offerings. This is a hands-on leadership role for technologists who combine deep engineering capability with client engagement and commercial ownership, delivering measurable enterprise impact beyond proof-of-concept initiatives. Responsibilities Lead the full AI lifecycle - from pre-sales solutioning (RFPs, proposals, scoping/pricing) through production delivery of enterprise ML/GenAI programs, on time and on budget Provide hands-on technical leadership in AI Engineering, driving design, development, and implementation of solutions across client engagements Serve as a trusted AI advisor to client stakeholders (including C-level), championing enterprise-wide AI adoption and translating business challenges into actionable AI strategies Collaborate cross-functionally and across geographies to shape scalable AI offerings, products, and differentiators for target verticals Requirements Strong hands-on AI expertise with a track record of production delivery (model architectures, quality metrics, MLOps); proficiency in Python and frameworks such as PyTorch/TensorFlow; familiarity with platforms like GCP, AWS, Databricks, or Azure Demonstrated leadership in driving multi-dimensional teams and influencing senior stakeholders to secure funding and deliver AI products Knowledge of semantic technologies (Ontology, Knowledge Graphs, OWL, RDF, SPARQL, SHACL) is a strong plus Excellent communication and problem-solving skills - able to translate complex technical concepts and business requirements into practical, scalable AI solutions for diverse audiences Bachelor's/Master's in Computer Science, Data Science, or related field (or equivalent experience)