Artificial Intelligence Jobs in Cambridge, MA

The AI Engineer will develop AI/ML solutions for investment analysis, design applications, optimize models, and work with large datasets in healthcare and finance contexts.

Own product and engineering as a technical co-founder, writing production code and leading architecture, reliability, observability, AI delivery infrastructure, unit economics, roadmap execution, customer-facing technical representation, and founding-team hiring. The role focuses on scaling a managed AI voice platform for legal front desks, improving production reliability and cost efficiency, expanding AI staff capabilities, and meeting legal and privacy requirements through secure or self-hosted models.

Design and deploy generative AI workflows and multi-agent architectures for healthcare applications. Curate EHR and claims data, extract clinical variables from unstructured medical text, and develop evaluation pipelines for agent safety, accuracy, factuality, and compliance. Apply advanced machine learning, NLP, and LLM techniques to create trustworthy longitudinal datasets supporting autonomous care agents and clinical decision tools. Communicate technical findings to technical and non-technical stakeholders.

Build and scale production-grade AI and generative AI systems on AWS, including LLM applications, RAG pipelines, machine learning models, data pipelines, APIs, and MLOps workflows. Deploy, monitor, version, and retrain models while implementing responsible AI guardrails, governance, security, and compliance. Provide technical mentorship and collaborate with architects and business teams across insurance platforms.

Defines and guides secure, scalable AI architecture across enterprise applications, platforms, data, infrastructure, and operations. Designs reusable patterns for GenAI, RAG, vector databases, semantic search, agents, orchestration, integrations, observability, and governance. Provides hands-on technical direction through design reviews, proofs of concept, platform roadmaps, production readiness, and implementation guidance. Partners with business and technology teams to deliver AI-enabled solutions while ensuring security, privacy, reliability, compliance, auditability, and responsible deployment.

Lead Weli, an AI-native B2B WealthTech venture, as Co-Founder and CEO. Own strategy, customer development, pilots, pricing, product iteration, fundraising, team recruitment, and company culture. The role requires selling to RIAs and wealth management firms, converting pilots into paid customers, building go-to-market operations, and leading the seed raise with FutureSight’s venture-building support.

Lead Crossfoot, an AI accounting agent platform for small-to-mid CPA firms. Own venture strategy, customer development, product direction, fundraising, founding-team recruitment, and company culture. Partner with FutureSight’s embedded engineering, design, growth, and fundraising teams to launch the MVP, validate pilots, convert customers, establish go-to-market, and raise seed capital.

Lead Orbitwell as Co-Founder and CEO, setting strategy, defining the target market, pricing, positioning, and go-to-market approach. Own customer development, product iteration with engineering, fundraising, hiring, and company culture. Expand the product from initial design partners to creators, teams, and agencies while validating retention and willingness to pay. The role offers meaningful founder equity and venture-building support rather than a salaried executive position.

As an Applied Researcher II, you'll develop AI models, collaborate across teams, conduct applied research, and drive innovations in AI to improve customer experiences.

The Applied Researcher I role involves developing AI foundation models, collaborating with cross-functional teams, and conducting advanced research to enhance banking experiences with AI.

Lead design, development, deployment, and support of foundation model training and LLM inference platforms. Build similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, and scalability; contribute to technical vision and roadmap while partnering across engineering, research, product, and program teams.

The Senior Lead AI Engineer will develop and support AI components, lead a cross-functional team, and drive innovation in AI systems at Capital One.

As a Lead AI Engineer, you will design, develop, and support AI software components while partnering with cross-functional teams to deliver AI-powered products at Capital One.

Build and deploy AI and machine-learning capabilities for cyber threat hunting, anomaly detection, incident response, detection engineering, and security automation. Develop custom models, LLM applications, and agentic systems, managing the full production lifecycle from data preparation through monitoring. Partner with security, engineering, offensive security, and governance teams to evaluate emerging technologies, support responsible AI, advise leadership, and mentor technical staff.

Leads data science, AI, digital health, and analytics strategy for Immunology R&D. Partners with scientific, clinical, platform, and engineering teams to identify use cases, analyze workflows, evaluate emerging technologies, develop scalable solutions, and improve research execution and decision-making. The role focuses on healthcare, imaging, clinical, biomarker, real-world, and digital health data, including generative and agentic AI applications.

Leads Vertex’s enterprise strategy for digital discoverability across search engines and AI-powered answer platforms. Establishes AEO, GEO, AI-ready website, metadata, schema, taxonomy, structured content, and governance standards. Partners with digital, commercial, medical, analytics, legal, privacy, agency, and technology teams to improve retrieval, indexing, citation, visibility, and measurement. Evaluates emerging AI search and conversational technologies, translates insights into recommendations, and drives organizational adoption in a complex, regulated environment.

Lead commercialization and GTM for Mastercard's U.S. Mid-Market Accelerator partner-led solutions. Define regional strategy, identify and structure partners, secure approvals, drive cross-functional execution, manage contracts and Salesforce pipeline, monitor post-launch performance, and enable internal teams and issuers to accelerate adoption and revenue growth.

Lead and build an Enterprise AI organization to define strategy, platforms, governance, and standards. Deliver scalable AI platforms (LLM gateways, model registries, vector DBs), enable business adoption, embed responsible AI and compliance, partner across Security, Legal, Finance, and drive measurable AI use cases and ROI while managing a small, cross-functional AI architecture and engineering team.

Design, build, and deploy scalable ML pipelines for multimodal neuroscience data. Research, train, and deploy advanced deep learning and reinforcement learning models to predict brain states, detect pathological patterns, and generate personalized neuromodulation parameters. Select AI frameworks and cloud infrastructure, collaborate with computational neuroscientists, and contribute to IP and publications.

Lead US TMT business development with an AI focus: identify revenue opportunities from AI regulation, M&A, governance and data trends; develop client strategies, communications and targeted outreach; support pitches and major US TMT projects; coach and manage MBD colleagues; collaborate with partners and international teams to drive client relationships and revenue growth.

Lead policy strategy on blockchain, digital assets, and emerging technologies; advise cross-functional teams on regulatory, risk, and policy implications; engage regulators and industry groups; translate complex technical concepts for senior leaders and stakeholders to inform decision-making.

The role involves designing and developing AI software solutions, collaborating with cross-functional teams, and optimizing large-scale AI systems for performance and scalability.

Lead the development of AI-powered products by collaborating with cross-functional teams, designing AI components, and optimizing models for performance and scalability.

As a Sr. Lead AI Engineer, you will design, develop, and manage AI software components, working with cross-functional teams to advance AI applications at Capital One.

Lead AI Engineer responsible for creating and deploying AI solutions, collaborating with cross-functional teams to innovate AI-powered banking products, and driving the technical vision for foundational AI systems.