Artificial Intelligence Jobs in Cambridge, MA

Partner with teams to deliver AI-powered products, build foundation models, and conduct applied research to enhance customer experiences.

Lead design and build of scalable full‑stack AI enablement platforms and tools to accelerate engineering workflows. Champion experimentation, automation (code generation, testing, deployment), best practices, and cross‑team collaboration while mentoring engineers and delivering production‑ready solutions.

Lead design, build, deploy, and support scalable, responsible AI systems (foundation model training, LLM inference, similarity search, guardrails, observability). Collaborate with cross-functional teams, optimize model performance and cost, and shape technical vision and roadmap for foundational AI platform services.

Architect, develop, and integrate on-device and cloud AI/ML systems for surgical navigation. Lead model training, evaluation, and optimization; ensure regulatory traceability and V&V (IEC 62304/ISO 14971); collaborate across software, hardware, firmware, quality, and regulatory teams; mentor junior engineers and drive design/code reviews in Agile workflows.

Lead an AI engineering team to design, build, deploy, and support foundation-model and LLM-based systems. Oversee model training, inference, similarity search, guardrails, evaluation, observability, and scalability optimizations. Make build-vs-buy decisions across OSS and SaaS AI technologies, set technical vision and roadmap, and recruit, mentor, and retain engineering talent.

Lead design, roadmap, procurement, and scaling of Mastercard's on‑premise AI infrastructure. Architect compute, GPU, storage, and networking for training and low‑latency inference at petabyte scale; run RFIs/RFPs; define data center and cooling requirements; partner with data science, MLOps, security, and governance; influence executives and evaluate emerging AI infrastructure technologies.

As a Senior AI/ML Engineer, you will design and deploy LLM systems, collaborate with cross-functional teams, and manage model deployment in production environments.

Leads cheminformatics and applied AI/ML strategy across small-molecule discovery programs. Develops methods for hit identification, hit-to-lead optimization, DNA-encoded library analysis, virtual screening, predictive modeling, and generative design. Advises senior leadership, shapes platform capabilities and portfolio decisions, builds external partnerships, mentors computational scientists, and leads cross-functional scientific initiatives advancing drug candidates.

Configure and operate an enterprise AI control plane covering MCP and LLM gateways, governance, access controls, observability, agent registries, and lifecycle management. Onboard internal and vendor MCP servers, implement authentication and policy patterns, build usage dashboards, troubleshoot production platforms, and create standards, runbooks, and onboarding documentation. The role partners with business, security, architecture, platform, and application teams to enable secure, governed AI agent integrations.

Lead AI agent optimization efforts by designing systems that improve token efficiency, response time, reliability, and output quality. Build agentic coding systems, develop AI application patterns, own features end to end, collaborate with engineering and field teams, support the developer community, and create public technical documentation. Work across Python, TypeScript, Java, and Go while serving as a domain expert in agent design and optimization.

The Research Engineer will design and conduct experiments at the intersection of manufacturing and AI, developing workflows and integrated systems to enhance manufacturing processes and technologies.

Lead the transformation of Sales Support into a scalable, data-driven, AI-enabled capability. Modernize workflows, service models, and performance visibility while identifying practical AI and automation use cases. Shape commercial acceleration initiatives across customers, partners, and installed-base opportunities, creating repeatable playbooks and measurable execution plans. Influence stakeholders across Sales, Operations, IT, Data, Product, Finance, Supply Chain, and regional teams while driving adoption, accountability, and cross-functional execution.

Lead development and validation of computational biomarkers and predictive models using multimodal biomedical data, including radiology imaging, clinical, molecular, pathology, and real-world datasets. Apply machine learning, statistical modeling, representation learning, foundation models, and causal inference for patient stratification, outcome prediction, and clinically actionable insights. Collaborate with radiologists, oncologists, data scientists, statisticians, and other experts while communicating findings, assumptions, uncertainties, and limitations through publications and presentations.

Owns full-cycle enterprise and mid-market sales for an AI cloud inference platform, from prospecting and discovery through technical demonstrations, proposals, negotiation, and close. Builds relationships with CTOs, ML engineers, and infrastructure leaders; develops pipeline, forecasts accurately, maintains HubSpot CRM hygiene, expands existing accounts, represents the company at industry events, and collaborates with product, engineering, CRO, founders, BDRs, and DevRel to strengthen the go-to-market motion.

Design and run AI-first onboarding, enablement, and learning programs for Klaviyo engineering. Partner with Dev Infra, L&D, Recruiting, and Eng Leadership to operationalize AI in workflows, codify engineering practices, run experiments, measure impact, and scale training to improve developer velocity, quality, and satisfaction.

Lead development of next-generation AI systems for insurance automation, including document validation, voicebots, computer-use agents, and complex workflow orchestration. Set chatbot architecture and technical standards, build and deploy production automations, evaluate emerging AI technologies, and partner with OpenAI on voice models. Own LLM system reliability, including evaluations, regression prevention, latency, cost, and failure handling.

Lead the architecture and development of next-generation AI and automation systems for insurance quoting, customer support, document validation, voicebots, and complex external-system workflows. Set technical standards for chatbot platforms, evaluate emerging AI technologies, deploy production solutions, and partner with OpenAI on voice models and workflow automation. The role requires hands-on experience building reliable LLM systems with evaluations, regression management, latency optimization, cost controls, and failure handling.

Lead the architecture and development of next-generation AI systems for insurance automation. Set technical standards for chatbot and LLM systems, build document validation and workflow automations, expand stateful voicebots, evaluate emerging AI technologies, and deploy reliable production systems. Own system architecture, model evaluation, latency, cost, regression prevention, and failure handling while partnering with OpenAI on voice models and workflow automation.

Lead the architecture and development of next-generation AI systems for insurance automation. Build production automations for document validation, record disputes, voice interactions, and external system navigation. Set technical standards for chatbot systems, evaluate emerging AI technologies, partner with OpenAI on voice and workflow solutions, and ensure LLM systems handle evaluation, regressions, latency, cost, and failure scenarios effectively.

Lead the architecture and production deployment of next-generation AI and automation systems for insurance quoting and customer support. Build document validation, voicebot, workflow automation, and external-system navigation capabilities. Set technical standards for chatbot systems, evaluate emerging AI technologies, partner with OpenAI, and ensure reliable LLM operations through evaluations, regression management, latency optimization, cost control, and failure handling.

Build and lead next-generation AI systems for automated insurance quoting, customer support, document validation, voice interactions, and external system navigation. Set technical direction for chatbot architecture, evaluate emerging AI technologies, and deploy production LLM systems. Own automation outcomes end to end, including evaluation, regression prevention, latency, cost, and failure handling, while partnering with OpenAI on voice models and workflow automation.

Sell risk and fraud software to small and mid-size corporate accounts in the Boston/NH territory. Prospect new business, execute account plans, manage the full sales cycle from outreach to renewal, maintain Salesforce CRM, engage C-level stakeholders, collaborate cross-functionally, and meet revenue targets while supporting in-person and virtual client meetings.

Provide expert legal and business research to attorneys and staff using advanced research tools; advise on research strategy; manage research workflow; develop training, onboarding, newsletters, and intranet content; evaluate and recommend online resources; support continuous learning and Research Services initiatives.

Leads AI-driven quality engineering for the my.harvard portal. Designs agents that analyze requirements, code, documentation, and defects to generate test scenarios and automation. Develops RAG pipelines, code-aware testing, human-in-the-loop validation, and autonomous test workflows using Python and modern testing frameworks. Maintains UI, API, regression, performance, accessibility, and CI/CD testing while improving agent performance through feedback and continuous learning. Collaborates with developers, architects, business analysts, product owners, and DevOps engineers.

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.