Top AI & Machine Learning Jobs in Boston, MA

Lead deal-strategy engagements across M&A, divestitures, and restructuring. Analyze markets, build financial models, identify risks/opportunities, design value-creation strategies, manage projects, and mentor teams while leveraging technology and innovation to drive client outcomes.

Lead delivery of AI-driven property & casualty insurance operations solutions: analyze client needs, design and implement software and AI architectures, manage projects and teams, coach staff, run training, ensure adoption, and drive process innovation while maintaining governance and standards.

Lead design and delivery of enterprise AI solutions including architecture, LLM integration, RAG, data pipelines, cloud deployment and governance. Oversee multiple projects, maintain executive client relationships, drive business development, mentor teams, and promote innovation across the PwC Network.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

Own AI-focused software product lifecycle from definition through release and end-of-life. Collaborate with cross-functional teams to conduct market and customer analysis, develop business cases and go-to-market plans, apply analytics and business process modeling, prioritize AI product backlogs, and manage stakeholder relationships to drive commercialization and growth.

Use advanced analytics, statistical methods, and machine learning to transform large datasets into actionable insights. Build data solutions and pipelines, perform exploratory analysis, create visualizations, validate models (including generative AI and NLP), collaborate with clients, mentor juniors, and maintain data quality to inform strategic decisions.

Lead design and delivery of enterprise AI and cloud solutions: analyze client requirements, develop technical designs, implement Azure-based architectures, lead project planning and execution, mentor teams, evaluate new technologies, and maintain professional standards while building client relationships.

Lead design and delivery of AI and blockchain-enabled integration and platform architectures. Analyze requirements, create technical designs and cloud strategies (Azure), direct large projects, validate outcomes with clients, coach and manage diverse teams, perform feasibility and business process modeling, and drive enterprise architecture and system integration initiatives to support audit automation and strategic technology roadmaps.

Lead data science initiatives within Data and Analytics Engineering to build predictive models, maintain data pipelines and lakes, apply ML/DL and generative AI, ensure data quality, coach teams, manage project timelines, and collaborate with stakeholders to drive data-driven business growth.

Lead QA for AI-enabled software: design and execute test strategies, identify and resolve defects, perform functional/compatibility and model-output testing, automate tests (e.g., Selenium), analyze data to inform recommendations, support post‑go‑live issues, and mentor junior team members while managing client expectations.