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 BonusThe 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
