Top Tech Jobs & Startup Jobs in Boston, MA

Leads complex projects and sales opportunities, improves operations infrastructure, expands client relationships, and identifies new revenue opportunities. Advises business leaders using complex data and insights, reviews deliverables, mentors junior colleagues, and drives operational change, risk management, compliance, controls, and continuous improvement across departments.

Lead technical projects and design, build, and deploy production-quality AI/ML systems, pipelines, and LLM-based agent platforms. Explore data, develop AI solutions, advise partners on proposals, select appropriate modeling approaches, establish evaluation and observability frameworks, optimize system performance and cost, and guide proprietary AI/ML infrastructure development. Engage directly with clients across industries while promoting best practices, responsible AI governance, and robust engineering standards.

Lead design and delivery of production-quality AI/LLM systems and pipelines. Work with clients and partners to craft solutions, build and deploy agent-based LLM systems, implement observability and evaluation, and promote best practices in modelling, code hygiene, and data engineering.

Lead regional execution of AI enablement: manage workflows, coaching, triage, experimentation, stakeholder coordination, and team development to drive adoption of firm AI products and scalable best practices.

Leads commercial effectiveness consulting engagements focused on pricing, go-to-market strategy, sales force effectiveness, marketing effectiveness, and revenue growth. Responsibilities include structuring complex problems, conducting quantitative and qualitative analyses, developing client recommendations, managing workstreams and teams, building client relationships, supporting business development, and contributing to thought leadership. Engagement Managers additionally lead projects, client relationships, commercial processes, and team development.

Own full-cycle recruiting for experienced hires in the Data & Analytics practice. Source, screen, and close technical talent (Data Scientists, Data Engineers, ML/AI specialists, analytics consultants). Partner with practice leaders on workforce planning, provide market intelligence and compensation guidance, manage ATS and reporting, coordinate interviews and offers, and support onboarding and talent strategy.

Develop and productionize underwriting analytics, predictive models, and decision tools using statistical and machine learning techniques. Partner with underwriting, broking, actuarial, and portfolio teams to perform feature engineering, exploratory analysis, model validation, visualization, and monitoring to support risk segmentation, portfolio insights, and underwriting optimization.

Lead life insurance product development and pricing engagements, grow client relationships, originate business, review financial projections, provide thought leadership, support M&A and reinsurance transactions, partner with strategy teams, and manage and develop project staff.

Lead and manage supply chain operations engagements: develop hypotheses, run analyses and modeling, synthesize insights into presentations, manage small teams (2–4), support partners on delivery, and help develop proposals and client relationships. Drive operational improvements across sourcing, planning, manufacturing, logistics, and IT-enabled supply chain solutions.

Lead client engagements for telco and AI initiatives: manage project delivery, coach teams, drive commercial relationships, identify business development opportunities, and apply quantitative analysis (SQL/Python) and AI capabilities to deliver strategic recommendations.