Top AI Jobs in Boston, MA

Lead the design and implementation of Microsoft Dynamics ERP solutions, manage large-scale projects, and innovate processes to enhance operational efficiency and client outcomes.

The Junior Customer Success Manager is responsible for developing relationships with customers, addressing concerns, presenting solutions, and coordinating sales efforts to drive product value.

Lead the sales team, drive direct sales to new clients, establish sales objectives and quotas, train staff, and maintain professional knowledge.

Responsible for architecting the sales data ecosystem, ensuring data integrity, governance, and providing real-time insights for forecasting and revenue decision-making.

The co-op involves owning and delivering AI projects, conducting data analysis, building workflows, and communicating insights to stakeholders over a 6-month period.

The Lead AI Engineer will design and develop AI software components, optimize large-scale production AI systems, and contribute to the technical vision for AI solutions at Capital One.

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 role involves leading AI solutions development, optimizing AI systems, and collaborating with cross-functional teams to enhance customer interactions at Capital One.

In this role, you will design, develop, and support AI software components, collaborate with cross-functional teams, and contribute to the roadmap for foundational AI systems.

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 cross-functional teams to develop and deploy AI-powered products, focusing on model training, inference, and system optimization. Innovate AI solutions that enhance banking experiences and use cutting-edge technologies to lead in AI engineering.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

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.

Lead strategy and vision for advanced orthopaedic technologies. Conduct market and customer research, scout and build partnerships, prioritize opportunities, govern initiatives, and partner with R&D, BD, supply chain, quality, and regulatory. Support technology integration into product teams, communicate with senior leaders and external partners, and manage multiple projects. Role requires OR/cadaver work and significant domestic/international travel.

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.

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.

The AI Engineer designs and deploys AI automation tools, partners with teams for workflow automation, and enhances operational efficiency using generative AI and data-driven decision support.

Develop regulatory strategies for SaMD, AI/ML-enabled and wearable health products. Advise cross-functional teams on regulatory implications, support FDA and EU submissions, engage authorities, monitor evolving guidance, and shape scalable compliance approaches for novel digital health technologies.

Responsible for designing and developing AI solutions for Oncology R&D, collaborating with scientists to translate complex questions into actionable insights, and contributing technical expertise in rapidly prototyping AI applications.

Lead the Oncology AI product strategy and roadmap, manage AI engineering teams, and drive stakeholder engagement for impactful AI solutions in R&D.

The role involves building AI-enabled solutions, developing data pipelines, and collaborating with teams to enhance Oncology R&D workflows.

Lead an AI engineering team to design, build, deploy, and optimize large-scale generative AI systems. Oversee foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and make strategic build-vs-buy decisions. Drive technical vision, roadmap, and talent development while ensuring scalable, cost-efficient, and responsible AI production systems.

Lead design, develop, deploy, and support foundational AI systems (LLM training/inference, similarity search, guardrails, observability). Partner cross-functionally to optimize scalability, cost, latency, and throughput, apply state-of-the-art research to production, and shape long-term AI platform roadmap.

Support biopharmaceutical drug product manufacturing by ensuring cGMP compliance, providing on‑floor operational support, driving investigations and CAPAs, managing tech transfer, change control, validation, documentation, and continuous improvement using Lean/Six Sigma; train staff, track KPIs, and support audits and inspections.

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.