The Practice Head – AI/ML will define and execute the strategic roadmap for Data \& AI, build and scale high\-performing cross\-functional teams, and spearhead innovation in AI/ML. The role involves end\-to\-end ownership – from solution architecture and delivery to client engagement and business growth.
This is both a leadership and client\-facing role, requiring the ability to translate business problems into scalable AI/ML solutions, while shaping offerings and positioning the organization as a leader in Data \& AI.
Define and execute the strategic roadmap for AI/ML and Data practices.
Build, mentor, and lead teams across data engineering, data science, ML engineering, and architecture.
Establish scalable frameworks, reusable assets, and best practices for AI/ML delivery.
Collaborate with executive leadership to shape offerings and expand the practice.
Lead end\-to\-end solution architecture: data ingestion, transformation, model development, deployment, monitoring.
Ensure solutions are robust, cost\-efficient, scalable, and aligned with client goals.
Translate business problems into AI/ML use cases with measurable ROI.
Act as a trusted advisor to clients on AI/ML strategy, adoption, and innovation.
Drive pre\-sales activities: proposals, solution presentations, stakeholder discussions.
Identify and execute cross\-sell / up\-sell opportunities across Data, Analytics, and AI.
Represent the organization at conferences, industry forums, and client workshops.
Deep experience in Data Engineering: ETL/ELT, Big Data (Spark, Hadoop, Kafka), SQL optimization, Data Lakes/Warehouses (Snowflake, Redshift, BigQuery, Databricks).
Proven track record in Data Science \& ML: supervised/unsupervised learning, deep learning, NLP, Computer Vision, Generative AI.
Hands\-on expertise with cloud platforms (AWS, Azure, GCP) and their native AI/ML services.
Strong knowledge of MLOps, CI/CD pipelines, model lifecycle management, and data governance.
12\+ years in technology with 5\+ years in AI/ML leadership roles.
Experience managing diverse teams across engineering, science, and architecture.
Proven success in solutioning, delivery management, and client engagement.
Exceptional communication, presentation, and stakeholder management skills.
Ability to articulate AI/ML business value to technical and non\-technical stakeholders.
A visionary leader with a proven record of building and scaling Data \& AI practices.
Strong blend of technical depth and business strategy.
Skilled at mentoring, inspiring teams, and fostering innovation.
Capable of shaping thought leadership in the AI/ML domain.
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