Top AI Jobs in Boston, MA

Lead and manage data science teams to build ML and deep learning models, maintain data pipelines and lakes, ensure data quality, deliver actionable insights, and manage project timelines and client expectations.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead design and delivery of conversational and agentic AI solutions for client contact centers. Guide cross-functional teams to build NLP interfaces, prototype UIs, run usability testing, ensure data integrity and security, and advise clients strategically. Coach teams, manage large projects, and drive adoption of AI-powered contact center technologies to improve client experience and operational outcomes.

Lead design and delivery of conversational and agentic AI solutions for client contact centers. Manage teams, mentor junior staff, gather requirements, design UIs, run usability testing, and implement AI integrations to improve customer experience and product adoption.

Lead design, build, and operation of scalable, secure AI-enabled platforms; mentor engineers; ensure reliability, security, and delivery of conversational AI and cloud-native solutions; collaborate cross-functionally to translate use cases into platform capabilities.

Lead design, development, deployment, and support of large-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize LLM performance and scalability, partner with cross-functional teams, and contribute technical vision and roadmap for foundational AI systems.

Lead design, build, deploy, and support GenAI platform services (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize LLM performance and scalability, collaborate cross-functionally, contribute to technical vision and roadmap.

Lead and deliver large-scale AI/ML programs and the next-generation Generative AI platform. Build and grow a world-class TPM discipline, manage cross-functional delivery, mitigate technical risk, and drive execution across product, engineering, design, and data science to achieve business impact in regulated environments.

Lead product efforts to modernize finance systems by driving AI and automation initiatives. Define product strategy, ensure compliant, audit-ready deliveries, collaborate cross-functionally, and measure operational leverage from automation and AI-enabled solutions.

Build and ship full‑stack web features and microservices for a cloud‑native genomics platform. Lead design and code reviews, mentor engineers, and develop production LLM applications (RAG, evaluation, citations) using managed endpoints and containerized CI/CD deployments. Collaborate with Product, QA, and Architecture to deliver reliable, regulated healthcare software.

Design and implement AI systems and scalable machine learning models, perform data wrangling and software engineering to deploy AI solutions, interpret data for client recommendations, collaborate across teams, uphold technical standards, and build client relationships while navigating complex, ambiguous problems.

The Enterprise Architect will design scalable AI solutions, mentor teams, support business development, and manage client relationships while evolving technology practices.

Lead design, build, and operate scalable GenAI platform components including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Collaborate cross-functionally, invent LLM optimization techniques, and shape long-term technical vision for foundational AI systems.

Leads the design, development, deployment, and support of foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Develops optimization techniques to improve scalability, latency, throughput, hardware utilization, and cost. Partners with research, engineering, product, and program teams; contributes to technical vision; and mentors engineers while applying emerging AI research in production.

Design and implement AI systems and scalable ML models (Python, TensorFlow); build/maintain data pipelines and integrations; apply NLP (NLTK) and deep learning for analytics; deploy and optimize models (including open-weight LLMs); collaborate with stakeholders and continuously learn to improve AI solutions and deployment reliability.

Secure Hi Marley’s internal AI environment by threat-modeling LLM integrations, agents, MCP connectors, and data pipelines; enforcing isolation, least privilege, and data boundaries; conducting AI red-team testing; managing AI tool governance; maintaining incident response runbooks; and producing SOC 2 and ISO 42001 compliance evidence. Partner with AI Operations and IT on access controls, cloud workload isolation, DLP, monitoring, and safe AI usage guidance.

Own DigitalOcean’s enterprise AI-native architecture, including agent orchestration, shared AI platform services, tool and capability layers, enterprise-system integrations, identity, authorization, governance, observability, evaluation, and cost controls. Build production prototypes and reference implementations, write code, establish technical standards, mentor distributed engineers, and re-engineer business workflows with functional teams. Partner across platform engineering, security, identity, data, and business technology to deliver governed, scalable agentic systems.

Lead enterprise strategy and hands-on delivery of AI-enabled solutions across clinical development. Partner with clinical, biostatistics, data science, regulatory, and digital teams to design, validate, deploy, and govern AI/ML, generative and agentic AI, predictive analytics, and workflow automation to improve trial design, operations, regulatory readiness, and decision-making. Build cross-functional teams, engage regulators and external partners, and drive organizational adoption and governance.

Lead program design and delivery for DTC data and AI initiatives: manage Snowflake-based data pipelines, build and deploy AI tools, design processes, ensure measurement governance (GA4), and align stakeholders to drive commercial growth.

Design, build, deploy, and support large-scale AI systems including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. Collaborate cross-functionally, optimize model performance and cost, and contribute to technical vision and roadmap for foundational AI platforms.

The role involves designing, developing, and supporting AI software components, leveraging various AI technologies, and optimizing performance for large-scale AI systems.

The role involves architecting a scalable AI platform, building distributed compute solutions, optimizing technologies, and mentoring internal talent in AI and ML.

As a Senior Lead AI Engineer, you will develop AI solutions, partner with cross-functional teams, optimize LLM performance, and contribute to the AI vision at Capital One.

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.

Conduct applied research and develop AI foundation models, including large language models and agentic AI systems. Responsibilities span model design, training, evaluation, validation, optimization, deployment, and scaling. The researcher collaborates with data scientists, engineers, and product managers to translate advanced AI research into customer-facing products, deliver platform and solution code, evaluate emerging methods, and independently pursue impactful research agendas.