Artificial Intelligence Jobs in Cambridge, MA

Lead end-to-end delivery of custom technology solutions across supply chain functions (planning, manufacturing, warehouse, logistics, merchandising). Define architectures and roadmaps, identify agentic AI use cases, guide development/testing/deployment, lead cross-functional teams, manage scope/timelines/budgets, and run client workshops to translate technical solutions into business outcomes.

Lead design and delivery of MassMutual's AI platform components (LLM gateway, model serving, multi-tenant compute). Own architecture, technical execution, reliability (SLOs/observability), governance controls, and cross-team alignment. Provide technical leadership through design reviews, ADRs, and hands-on pairing.

Provide corporate and transactional legal support for technology and corporate initiatives, drafting and negotiating complex technology and commercial agreements, advising on AI procurement and data privacy (HIPAA, state laws), supporting governance, investment due diligence, and legal operations improvements.

The role involves leading AI and advanced analytics initiatives in life sciences, managing client relationships and P&L, developing strategies for growth, and contributing to the team's thought leadership while enhancing analytical models and solutions.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead M&A, divestiture, and restructuring advisory engagements; analyze market trends and financials; develop strategic frameworks; guide deal value creation and post-merger integration; coach and direct teams; communicate recommendations to clients and stakeholders.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

The Technology Consultant will deliver technology solutions for Supply Chain and Manufacturing, focusing on data strategies and digital transformation across enterprises. This role involves leading projects with modern technologies and mentoring teams for continuous professional development.

As a Lead AI Engineer, you will develop and support AI products, enhance system performance, and collaborate across teams to innovate AI solutions for Capital One.

The AI Engagement Manager will lead strategic relationships with clients to implement AI solutions, driving business transformation and optimizing operations in the housing sector.

Lead AI Engineer responsible for developing AI-powered products, optimizing large language model inference, and collaborating across teams to enhance customer interactions and business value.

Lead AI Engineer responsible for designing and developing AI-powered products, utilizing ML algorithms, and optimizing large-scale AI systems. Collaborate with cross-functional teams to enhance customer experience and drive AI initiatives at Capital One.

Lead and grow an AI engineering organization building foundation-model training and LLM-powered production systems. Own design, deployment, optimization, evaluation, governance, and observability of scalable AI platforms; make build-vs-buy decisions across open source and SaaS AI technologies; drive technical vision and mentor engineering teams to deliver responsible, high-performance AI capabilities.

Lead design, build, deploy, and support foundation model training and LLM inference systems, similarity search, guardrails, evaluation, and observability. Optimize production AI for scalability, cost, latency, and throughput. Collaborate cross-functionally, mentor engineers, and shape long-term foundational AI technical vision and roadmap.

Provide strategic legal counsel for onboarding, due diligence, sales practices, and controls for alternative investments, complex products, and digital assets. Draft and negotiate sponsor agreements, develop policies and procedures, perform legal research and memoranda, and collaborate with Compliance, Product Due Diligence, Risk, and Supervision teams to ensure regulatory compliance for the broker-dealer and investment advisory businesses.

Leads enterprise AI strategy and execution by identifying opportunities, building business cases, defining product vision and roadmaps, and guiding AI product development. Partners with business, data science, and technology teams to deliver customer-driven solutions, translate stakeholder needs, prioritize initiatives, and support innovation. The role also mentors team members, applies design thinking and UX practices, and evaluates build, buy, and partnership options.

Lead the global AI vision and roadmap for SS&C’s contact center. Design, deploy, and optimize virtual agents, agent assist, conversational AI, analytics, and automation integrated with NICE infrastructure. Partner with technology, operations, compliance, HR, and legal teams to ensure scalable, secure, ethical, and regulatory-compliant solutions. Identify opportunities to improve customer journeys, self-service, colleague productivity, customer satisfaction, and operational efficiency while establishing governance, standards, and measurable success metrics.

Own strategic enterprise client relationships, retention, renewals, upsell, cross-sell, and account expansion for a B2B SaaS portfolio. Develop account plans, understand customer objectives and competitive landscapes, create demand, build value-based business cases, manage MEDDPICC sales processes, and coordinate internal stakeholders. The role requires executive communication, enterprise selling expertise, Salesforce Agentforce 360 proficiency, quota achievement, and 7–10 years of relevant experience. It is hybrid in Boston and requires travel as needed.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

The Product Marketing Director will lead product marketing strategy, positioning, messaging, go-to-market execution, market research, launches, and post-launch optimization. The role serves as an Adobe technology subject matter expert and develops joint solutions with Merkle services. Responsibilities include cross-functional collaboration, KPI analysis, stakeholder engagement, competitive intelligence, and reporting to senior leadership. The position requires translating complex technical capabilities into customer benefits and driving product awareness, adoption, and growth.

Lead a global strategic client sales team serving major financial services organizations across buy-side and sell-side markets. Own aggressive revenue targets, account strategy, forecasting, pipeline development, enterprise sales execution, and team performance across NAMER, EMEA, and APAC. Build senior client relationships, coordinate cross-functional resources, support trials, strengthen brand awareness, and relay market and product needs to internal teams. The role includes regular global travel.

Conduct computational research applying first-principles modeling, atomistic simulations, AI, and scientific machine learning to discover and optimize organic electronics materials. Investigate charge transport, excited-state behavior, morphology-property relationships, and device performance. Build predictive models, connect simulations with experiments, generate materials hypotheses, and collaborate with AI, software, computational, and experimental teams to develop autonomous scientific discovery workflows.

Lead design, development, deployment, and support of foundational AI systems including LLM training and inference, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI performance (latency, throughput, cost), collaborate cross-functionally, and contribute to technical vision and roadmap for production AI infrastructure.

Provides strategic and technical statistical leadership across the pharmaceutical CMC lifecycle, including process and analytical development, manufacturing, validation, stability, quality control, and regulatory submissions. Establishes a CMC Statistics Center of Excellence, defines governance and best practices, applies DOE, SPC, regression, multivariate, predictive, and advanced analytics methods, and supports investigations and regulatory interactions. Partners across development, manufacturing, quality, regulatory, and digital organizations while building statistical capabilities and training programs.