As Practice Manager, AI & Data you will be responsible for; Practice Leadership & Management - Lead and manage the AI & Data practice - Manage and steer the allocation of practice resources across multiple activities, including: - Technical pre-sales support - Technical expertise delivery to projects - Recruitment support - Training and competency development - Provide line management and leadership to members of the practice including technical leadership across AI and Data - Define skills development objectives for practice members and evaluate progress and effectiveness - Develop, improve, and standardize processes, methodologies, and tools - Foster a culture of collaboration, innovation, and knowledge sharing across the practice Client Engagement & Pre-Sales - Partner with Sales and Account teams to identify and shape AI & Data opportunities - Lead or contribute to solutioning, proposals, and RFP responses - Act as a trusted advisor in client discussions and executive forums - Align AI & Data solutions with business value and client outcomes Technical Leadership & Innovation - Provide leadership across advanced AI & Data domains: - Generative AI & LLM ecosystems (prompt engineering, RAG, multi-agent systems) - Data Engineering & Modern Data Platforms (ETL/ELT, streaming, data lakes, data mesh) - Cloud-based AI architectures (AWS, Azure, GCP AI services) - Machine Learning & Deep Learning (supervised, unsupervised, reinforcement learning) - Support delivery teams with hands-on guidance and expert oversight - Drive development of AI & Data offerings, accelerators, and reusable assets - Identify opportunities for AI-driven productivity gains and automation - Ensure adoption of industry best practices and scalable architectures Qualifications - 12-15 years of experience in consulting, engineering services, or technology-driven organizations - 5+ years of experience in AI, Data, or Analytics leadership roles - Proven experience building and scaling technical teams or practices - Experience in: - Generative AI technologies (LLMs, RAG pipelines, prompt engineering, API-based AI services) - AI/ML frameworks (e.g., Python ecosystem, TensorFlow, PyTorch, Scikit-learn) - Data Engineering tools & platforms (Spark, Databricks, distributed systems) - Cloud AI ecosystems (Azure AI, AWS SageMaker/Bedrock, Google Vertex AI) - MLOps / LLMOps tools (MLflow, Kubeflow, containerization, orchestration) - Understanding of data governance, security, and AI regulations Skills & Competency Management - Create, maintain, and manage the practice skill matrix - Identify competency gaps and develop capability-building plans - Develop and coordinate technical training programs and certification initiatives - Build and strengthen a team of experts through: - Recruitment - Coaching and mentoring - Internal talent development and training - Support career development planning and succession management within the practice - Promote technical communities, best practices, and continuous learning initiatives Educational Qualifications - Bachelor's degree (or higher) in Computer Science, Data Science, AI, or related field - Certifications in AI/ML, Cloud are a plus Salary Range: $160,000-$190,000 + Annual Performance Bonus The actual salary offered is dependent on various factors including, but not limited to, location, the candidate's combination of job-related knowledge, qualifications, skills, education, training, and experience