Top AI Jobs in Boston, MA

As a Lead AI Engineer, you will develop and support AI products, enhance system performance, and collaborate across teams to innovate AI solutions for Capital One.

Lead AI Engineer responsible for developing AI-powered products, optimizing large language model inference, and collaborating across teams to enhance customer interactions and business value.

The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging AI technologies, and pushing research developments into real-world applications.

Lead AI Engineer responsible for designing and developing AI-powered products, utilizing ML algorithms, and optimizing large-scale AI systems. Collaborate with cross-functional teams to enhance customer experience and drive AI initiatives at Capital One.

The Distinguished AI Engineer will develop and support AI software components, lead AI system architecture, and mentor teams, focusing on scalable AI solutions.

Lead design and implementation of conversational and agentic AI solutions for clients, building voice and natural language interfaces, prototypes, and responsive web front-ends. Conduct user research and usability testing, collaborate with cross-functional teams to integrate AI platforms (Dialogflow, Amazon Lex, Azure OpenAI, AWS Bedrock), and apply human-centered design to optimize contact center workflows and customer experiences.

Lead development and implementation of conversational and agentic AI solutions for contact centers. Manage cross-functional teams, translate client requirements into technical specs, design responsive UIs using AngularJS/React/Vue, run usability testing, apply human-centered design, and mentor junior staff while building client relationships to ensure successful delivery of AI-driven products.

The role involves developing, testing, and validating Generative AI agents and maintaining automated testing standards. Responsibilities include mentoring junior associates, analyzing complex issues, and applying governance controls in AI-driven solutions.

Lead development and implementation of AI-powered contact center and conversational solutions. Guide cross-functional teams to design natural language interfaces using Dialogflow and Amazon Lex, prototype UIs with Figma, conduct usability testing and user research, validate data integrity and security, build stakeholder relationships, and coach teams to deliver high-quality, client-aligned AI products.

As an AI Engineering Manager at PwC, you will lead the design and operation of AI-powered platforms, mentor engineers, and ensure project delivery excellence while focusing on security and scalability.

As an AI Business Systems Engineer, you'll apply AI solutions to optimize processes across departments, ensuring efficient organization-wide workflows and integrations.

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.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

The Sr. Distinguished AI Engineer at Capital One will lead the development and deployment of AI systems and collaborate with cross-functional teams to enhance customer experiences through AI solutions. Responsibilities include designing and supporting AI components and optimizing production AI systems.

Lead design, development, deployment, and support of production-scale AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, observability). Drive LLM optimizations, technical vision, and cross-functional delivery of responsible AI products.

Lead design and delivery of an agentic AI platform: define architecture, standardize agentic workflows, build GenAI SDK/CLI, harden guardrails and observability, optimize orchestration and costs, own Helm/K8s operators for autoscaling, incubate RFCs and proofs of concept, and mentor engineering leaders while evangelizing platform practices internally and externally.

Lead and scale AI engineering teams to design, build, deploy, and support foundational AI systems (LLM training/inference, vector search, guardrails, evaluation, observability). Drive technical vision, build-vs-buy decisions across OSS and SaaS, optimize LLM performance, and attract and develop top AI engineering talent.

Design and build an enterprise generative AI platform: agent orchestration, memory, guardrails, vector search, SDKs, and blueprints. Standardize agentic workflows, optimize orchestration and cost, own Helm/Kubernetes operators, ensure trust and safety, mentor engineering teams, and evangelize platform architecture internally and externally.

Use advanced analytics, statistical techniques, and machine learning to extract insights from large datasets. Design data solutions and pipelines, build predictive models (R, MATLAB), and apply TensorFlow and Scikit-Learn for deep learning and NLP. Collaborate with teams and clients, deliver quality work, and adhere to firm standards.

The AI Engineer will develop production-grade AI tools, bridge business needs with technical solutions, and mentor other engineers while ensuring scalability and security in AI integration.

The Senior Data Scientist will design and implement AI-enabled products using clinical trial data, mentor team members, and collaborate with stakeholders.

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

The AI Business Systems Engineer applies AI solutions across the company, integrating systems, mapping processes, and designing structured workflows to improve efficiency and decision-making.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.