Top Tech Jobs & Startup Jobs in Boston, MA

Lead partner analytics by building scalable dashboards, forecasting and ROI models, and experimental designs to evaluate and optimize partner performance. Collaborate with Product, BD, Marketing, and Data Engineering to improve pipelines, translate insights into recommendations, and mentor analysts to scale partner growth.

Set technical direction for Root’s AI platform, including infrastructure, tooling, shared services, governance, reliability, security, observability, and cost management. Lead cross-team initiatives, guide AI and LLM architecture decisions, establish operating standards, shape technical roadmaps, resolve complex tradeoffs, and mentor engineers and technical leaders across the organization.

Lead the AI Platform team in building reliable, secure, observable infrastructure, shared services, deployment patterns, and operational practices for AI capabilities. Set technical priorities, coordinate cross-team dependencies, guide architecture and production operations, improve developer experience, and coach engineers while contributing to complex technical work.

Lead Root’s AI Enablement Squad by defining AI-native ways of working, guiding cross-team adoption, connecting user workflows to AI Platform strategy, and turning experiments into reusable products and capabilities. Set technical direction, lead major initiatives, align senior stakeholders, establish adoption measures, promote responsible AI use, and mentor engineers and technical leaders across the organization.

Lead the AI Enablement Squad by prioritizing embedded AI adoption engagements, translating workflow discoveries into reusable AI Platform improvements, coordinating cross-functional partners, and coaching engineers. Establish repeatable adoption playbooks, protect capacity for scalable capabilities, communicate outcomes and blockers to stakeholders, and guide responsible deployment of AI solutions across the company.

Lead development of Root’s machine learning platform for insurance pricing. Build and operate feature pipelines, model training and orchestration, registries, validation, serving, observability, and reproducibility tooling. Partner with researchers to convert experimentation into reliable production systems, explore LLM-enabled data science automation, drive technical roadmaps and execution, and mentor engineers while maintaining high standards for reliability and correctness.

Lead the architecture and development of Root’s machine learning platform for insurance pricing. Build infrastructure for feature pipelines and stores, reproducible training and orchestration, model registries, serving, validation, observability, and research-to-production workflows. Establish versioned contracts and technical standards, automate workflows using LLMs, write and review critical code, influence cross-team strategy, and mentor senior engineers. Collaborate closely with data scientists and researchers to create scalable, reliable, and reproducible ML capabilities.

Lead and develop a team of partnership analysts; translate business questions into analytical frameworks, experiments, forecasts, and ROI models. Build dashboards and reporting infrastructure, analyze cohorts, funnels, retention, and partner performance, and own measurement frameworks for growth initiatives. Partner with Business Development, Engineering, Product, and Marketing to shape partnership strategy and communicate data-driven insights to technical and non-technical leaders.

Analyze and optimize digital partnership performance, growth, profitability, and customer acquisition economics. Design experiments, develop forecasts and performance models, build measurement frameworks, investigate anomalies, and provide actionable recommendations. The role requires translating ambiguous business questions into analytical solutions, communicating insights to technical and non-technical stakeholders, and establishing scalable analytical processes that support strategic decision-making.

Leads Root’s Telematics Technology engineering domain, overseeing telematics data platforms, feature stores, trip pipelines, APIs, and customer-facing experiences. Responsibilities include setting technical strategy and roadmaps, partnering with Data Science, Pricing, and Underwriting, managing and developing engineering teams, recruiting, guiding distributed-system architecture, and improving reliability, observability, scalability, delivery processes, and production stability. The role also drives AI-tool adoption and may oversee production machine-learning systems.