Top AI Jobs in Boston, MA

Own strategy and roadmap for Crunchbase's customer-facing AI data layer. Identify and validate model-derived data products, lead cross-functional development, set quality standards, drive adoption and monetization, and monitor performance and product economics.

Drive go-to-market strategy and adoption for Kensho AI products by bridging technical AI capabilities and commercial teams. Lead customer demos, technical deep-dives, co-development partnerships, market analysis, and sales enablement while feeding product and strategy teams with market insights to expand revenue and partnerships.

Lead global strategy to optimize and modernize financial crime detection across transaction monitoring, customer risk rating, and fraud models. Drive transition from rules-based controls to AI/ML-driven detection, oversee model lifecycle governance, reduce false positives, ensure regulatory defensibility, and partner with Compliance, Technology, Data, Operations, and vendors to deliver measurable risk and operational improvements.

Lead and grow an AI Platform engineering team delivering cloud-native infrastructure for AI/ML development. Own people leadership, hiring, roadmap delivery, architecture reviews, engineering standards, stakeholder communication, and team wellbeing while partnering across AI, product, and cloud teams.

The AI Lab Research Engineer will develop scientific AI models for complex problems, design and deploy AI agents, and collaborate across disciplines in a lab environment.

As an AI Research Scientist II, you will develop and prototype AI solutions, advance drug design campaigns, and publish research while collaborating cross-functionally on cheminformatics and bioinformatics.

Lead product strategy for Suno's research org by defining evaluation frameworks, connecting creator needs to model capabilities, prioritizing research, running experiments, and bringing model improvements to market in partnership with researchers and cross-functional teams.

The AI Automation Engineer will automate internal processes, mentor non-technical staff on building tools, and ensure solutions deliver measurable business impact using AI technologies.

The AI Solutions Architect engages in technical pre-sales, designing AI architectures, conducting technical discovery sessions, and collaborating on proof-of-concept projects while ensuring smooth transitions to delivery teams.

Join Research Innovation to build and support AI assistants, agentic applications, and citizen development tooling. Provide user support, design training and workflows, work with engineering on enterprise agentic software, and teach non-technical colleagues. Adapt to shifting priorities and contribute ideas to scale AI tooling across the research organization.

Design and build agentic AI features by integrating LLM APIs into product workflows. Write well-tested TypeScript across the stack, implement tool invocation and multi-step reasoning flows, collaborate with Product and Design, and improve reliability and performance of agentic systems while documenting findings.

Lead GTM strategy for AI products, drive sales implementation and adoption, define KPIs/OKRs, enable teams with agentic AI workflows, and translate technical capabilities into measurable business outcomes across cross-functional stakeholders.

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

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.

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 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 AI Test & Evaluation programs that measure mission-level outcomes across models, subsystems, and user workflows. Architect T&E systems, advise government customers, translate findings into engineering recommendations, run program execution (schedule/budget/team), and grow business opportunities while leading a multidisciplinary technical team.

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.

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.

As a Research Manager at CBAI, you will support fellows in AI and biosecurity research by providing feedback, managing projects, and facilitating resource connections. You will also contribute to program management and development, ensuring fellows succeed in their research goals.

The AI Operations Associate monitors AI-driven workflows, investigates incidents, supports operational controls, and recommends improvements to maintain workflow reliability and safety in finance environments.

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.