Top AI Jobs in Boston, MA

As a Staff Product Manager, you'll drive the strategy and success of SIEM products, collaborating with various teams to fulfill customer needs and market demands while focusing on security for SMBs.

Leads the internal audit function, developing and executing COSO/IIA risk‑based audit plans, reporting to the Audit Committee, liaising with regulators and external auditors, managing anonymous reporting investigations, conducting quality assessments, overseeing audit budget, and developing an audit team to strengthen controls across operations, compliance, and finance.

As Product Manager II for AI & Data Security, you'll own the roadmap for AI capabilities, manage security posture, collaborate with engineers and researchers, and engage customers to enhance AI systems security.

Own and grow Dynatrace's AI-native partner ecosystem for app builders and AI SaaS. Build executive relationships, execute co-sell motions, drive partner-influenced pipeline and revenue, run joint GTM campaigns, support events and enablement, and collaborate with Product on AI observability integrations and roadmap.

Design, prototype, and implement quantitative models and data-driven trading analytics using statistics, machine learning/AI, and time series forecasting. Develop code, product specs, and processes; collaborate with Global Markets stakeholders and tech teams; rigorously test model efficacy and deliver polished presentations to drive adoption.

Lead and execute AI integration across finance and legal, owning strategy, sequencing, and delivery. Build and lead embedded AI Fellows, productionalize LLM-driven tools, drive adoption, measure business impact, and coordinate with external partners to consolidate initiatives and ensure enterprise readiness.

Lead enterprise AI integration across Product Development and Product Excellence. Build unified data infrastructure, deploy AI tools, reform program management, scale AI-powered quality and consumer insights, and lead an embedded AI Fellows team to drive adoption, measurable outcomes, and organizational change across hardware and consumer product lifecycles.

As a Senior Lead AI Engineer, you will design and develop advanced AI systems, collaborate with cross-functional teams, and introduce innovative AI techniques while mentoring others.

The Lead AI Engineer will develop AI solutions, partner with cross-functional teams, and optimize large-scale production AI systems using various technologies.

The Senior Lead AI Engineer will collaborate with cross-functional teams to design, develop, and implement AI software solutions, focusing on large-scale production systems and AI model optimization.

As a Lead AI Engineer, you will develop, deploy, and support AI software components, collaborate with cross-functional teams, and optimize performance of large-scale AI systems.

The Lead AI Engineer will design, develop, deploy, and support AI software components, collaborating with cross-functional teams to create scalable AI solutions that enhance customer interactions and operational efficiency.

The Lead AI Engineer will develop and deploy AI software components, optimize AI systems, and collaborate with cross-functional teams at Capital One to enhance customer interactions through AI technology.

The Senior Lead AI Engineer will design, develop, and support AI systems, leveraging machine learning technologies to enhance customer experiences and optimize AI performance.

Lead AI Engineer to design, build, deploy, and support production-scale vision and foundation-model components (training, inference, vector search, guardrails, evaluation, observability). Partner with cross-functional teams, optimize LLM training/inference for cost/latency/throughput, and help set the technical vision and roadmap for foundational AI systems at Capital One.

Design, develop, deploy, and support foundational AI systems (foundation model training, LLM inference, similarity search, guardrails, evaluation, observability). Optimize training/inference for scalability, cost, latency, and throughput. Partner cross-functionally to deliver production AI services and shape the technical vision and roadmap for foundational AI at scale.

Lead design, develop, test, deploy, and support foundational AI systems including foundation model training, LLM inference, similarity search/VectorDBs, guardrails, evaluation, observability, and optimization for scalability, cost, latency, and throughput. Partner cross-functionally and contribute to technical vision and roadmap.

Lead Applied AI/ML strategy and development for Internal Medicine Research, translating foundation models, agentic and multimodal AI into reusable, validated capabilities. Define governance, evaluation standards, prioritize high-value use cases, manage external partnerships, and drive adoption across IMRU while ensuring scientific rigor, reproducibility, and human oversight.

Lead modernization of enterprise AI/ML infrastructure and analyst workflows. Build agentic, scalable, secure platform services, integrate generative AI and low-code/no-code tooling, scale AutoML for tabular and time-series, and engineer automated governance and controls while mentoring teams and influencing cross-functional stakeholders.

Lead a cross-organizational program to transition engineering to an AI-driven, self-optimizing ecosystem with robust telemetry and evaluation. Orchestrate strategy and execution, mitigate technical risk, build and grow a TPM practice, align product/engineering/design/data science, and deliver measurable business impact.

Lead design, development, deployment, and support of scalable GenAI platform components (foundation model training, LLM inference, vector search, guardrails, evaluation, observability). Optimize training and inference performance, contribute to technical vision and roadmap, and partner with cross-functional teams to deliver responsible, production-grade AI systems.

Lead AI and GenAI data science engagements: perform advanced analytics, build predictive models, design data pipelines and warehouses, validate large datasets, produce data visualizations, coach teams, and advise clients on data-driven solutions and systems-level opportunities.

Lead product management activities for commercial and internal software products across the lifecycle. Support large enterprise software implementations and program delivery, maintain program controls, report on risks and finances, mentor junior staff, manage stakeholder relationships, and align project objectives with strategic goals while driving continuous improvement.

Entry-level AI Platform Engineer to contribute to cloud-based AI platform components, model serving, developer tooling, and reliability practices. Work with senior engineers on design, code, tests, documentation, and operational tasks while learning governance, access controls, and AI deployment patterns.

Lead development and deployment of foundational AI systems: design, build, test, and support LLM training and inference, similarity search, guardrails, observability, and optimizations for scalability, cost, latency, and throughput while shaping technical vision and collaborating with cross-functional partners.