Top AI Jobs in Boston, MA

Leads global data center capacity management across power, cooling, space, availability, and infrastructure. Manages forecasting, utilization optimization, DCIM-based inventory, reporting standards, physical audits, compliance readiness, SLAs, equipment lifecycle planning, and decommissioning. Builds and develops a team while influencing cross-functional partners and suppliers. Requires strong data center infrastructure knowledge, advanced spreadsheet analysis, capacity modeling, and experience using AI to improve workflows and decisions.

Leads Inato’s marketing organization and strategy, including account-based marketing for enterprise sponsors, integrated sales campaigns, product positioning, go-to-market execution, customer marketing, and advocacy programs. Establishes marketing goals and metrics tied to business outcomes while partnering with Sales, Product, Customer Success, Strategy, and executive leadership. Coaches and develops the marketing team, builds internal product marketing capabilities, and drives measurable pipeline creation, customer expansion, and market differentiation.

Leads technical pre-sales and foundational implementation engagements for SailPoint SaaS solutions. Discovers customer requirements, maps them to product capabilities, delivers proof-of-value implementations, explains architecture and best practices, and collaborates with sales, product, services, and customer success teams. Develops AI and agentic technology solutions for demonstrations and customer problems, while serving as a technical and consultative advisor to customers, partners, and colleagues.

Forward Deployed Engineers support sales and customer engagements by discovering requirements, designing and implementing foundational SaaS solutions, delivering proof-of-value implementations, and educating customers on architecture and best practices. They collaborate with sales, product, professional services, and customer success teams; use AI and agentic technologies to solve customer problems; lead technical engagements; document requirements; and develop reusable demonstration solutions. The role may require up to 15% travel.

Forward Deployed Engineers support enterprise sales and customer engagements by discovering requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value projects. They provide technical leadership, explain architecture and best practices, collaborate across sales, product, services, and customer success teams, and develop AI- and agentic-technology solutions for demonstrations and customer problems. The role requires strong client communication, software implementation expertise, SaaS architecture knowledge, and familiarity with enterprise infrastructure and identity governance.

Leads a team of Forward Deployed Engineers while supporting sales, customer discovery, solution architecture, foundational implementations, and proof-of-value engagements. The role translates customer requirements into SailPoint solutions, advises on product architecture and best practices, collaborates across sales, product, services, and customer success, and develops AI-powered agentic solutions for demonstrations and customer outcomes. It requires significant enterprise software implementation or presales experience, technical leadership, SaaS architecture knowledge, and client-facing consulting expertise.

Leads enterprise AI tooling and security engineering, designing scalable cloud platforms and secure AI applications. Responsibilities include protecting models, agents, prompts, data, APIs, and outputs; securing the AI/ML lifecycle; implementing identity, encryption, monitoring, threat detection, adversarial testing, and incident response; and establishing engineering standards. The role mentors engineers, influences architecture and technology strategy, and partners with governance, risk, compliance, and business teams to support responsible AI adoption.

Own the full sales cycle for Fieldguide’s AI audit platform across public sector organizations, initially focusing on federal accounts. Build territory and go-to-market strategy, navigate complex government procurement processes, exceed revenue targets, develop executive and practitioner relationships, and manage multithreaded enterprise deals. Collaborate cross-functionally to shape messaging, sales processes, and market expansion into state, local, and higher education sectors. The role is fully remote in the United States with up to 30% travel.

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Lead full‑stack development of React Native mobile apps and Node.js backends for digital therapeutics. Own architecture, build CI/CD and AWS infrastructure, design multi‑agent AI workflows, mentor engineers, and resolve cross‑cutting production issues.

Lead product strategy and execution for signals exploitation and tracking capabilities. Define roadmaps, shape backlogs with customers and product owners, support architecture and design reviews, and drive development and demonstration of advanced algorithms and software for DoD and Intelligence Community missions. Balance reuse, integrated system offerings, and component supply-chain opportunities while leading engineering teams through the Agile lifecycle and supporting technical marketing and business development.

Own the end-to-end integration and automation architecture for the MyCDW platform. Design ServiceNow integrations, APIs, event-driven patterns, middleware, data contracts, AI-agent guardrails, automated workflows, and observability. Establish governance, security, coding standards, testing, documentation, and reusable architecture patterns. Evaluate platforms, lead prototypes, resolve complex issues, manage vendors, influence stakeholders, and align solutions with business strategy, compliance requirements, scalability, resilience, and cost objectives.

Build and lead enablement programs for Customer Success and Implementation teams, including onboarding, product training, continuous learning, playbooks, and AI-enabled workflows. Identify performance gaps, translate product updates into practical training, improve adoption of tools and processes, and establish feedback loops with Product, Support, Customer Education, and Product Marketing. The role supports stronger renewals, expansions, customer outcomes, and operational efficiency in a growing SaaS organization.

Develop advanced personalization and recommendation systems for digital grocery shopping. Build, deploy, monitor, and maintain machine learning pipelines and microservice APIs supporting production inference. Apply natural language processing, generative AI, large language models, agentic AI, recommendation models, deep learning, transformers, and classical machine learning techniques to real-world business problems. Evaluate and tune models, communicate technical results, and contribute to scalable AI solutions.

Develop regulatory strategies for digital health, SaMD, wearable, and AI/ML-enabled products. Advise Product, Engineering, and AI/ML teams on regulatory pathways, claims, intended use, risk classification, software lifecycles, and clinical evidence. Lead or support FDA and EU submissions, including Q-Submissions, 510(k)s, De Novo requests, and EU MDR documentation. Monitor evolving regulations, engage with authorities, and communicate regulatory risks and opportunities to stakeholders and leadership.

Develop and maintain native iOS features powered by WHOOP Coach generative AI and data science algorithms. Build Swift applications, integrate RESTful backends, document architecture, monitor metrics and crashes, and manage app releases. Contribute to feature planning, stay current with Apple frameworks, develop shared tooling, and mentor junior engineers while collaborating with product, data science, and engineering teams.

Build and maintain backend infrastructure and member-facing generative AI features that deliver personalized health and performance insights. Collaborate with Product, Design, Analytics, and Data Science teams to define requirements and deliver scalable solutions. Develop reliable software using Java, Kafka, AWS, and PostgreSQL; design RESTful APIs and relational databases; optimize performance; and maintain observability and monitoring systems.

Lead research, development, and deployment of large-scale multimodal foundation models integrating wearable, language, biomarker, clinical, and behavioral data. Develop self-supervised and representation-learning methods, distributed training pipelines, and post-training techniques. Collaborate with engineering, MLOps, data, product, and research teams to operationalize robust, observable, privacy-preserving models and translate capabilities into member-facing features. Contribute to technical roadmaps and architectural decisions for WHOOP’s foundation AI systems.

Leads and manages an AI Quality engineering team responsible for evaluating and improving AI outputs. Defines testing frameworks for model performance and drift, establishes technical strategy and architecture, provides technical direction, manages technology vendors and partnerships, drives engineering quality improvements, and mentors team members.

Designs and operates Kubernetes clusters on AWS, builds scalable and secure AI runtime infrastructure, and develops tooling for developer productivity and automated development workflows. The role improves platform reliability, supports long-running tasks on cost-efficient infrastructure, partners with application, security, and data teams, participates in incident response, and provides technical leadership and mentorship across the Platform organization.

Build and scale WHOOP AI platform systems and member-facing experiences across the frontend and backend. Design scalable web applications, APIs, and intuitive interfaces; contribute to agent orchestration architecture; translate business requirements into reliable solutions; write tested code; and monitor, debug, and improve production performance and stability. Collaborate with product managers, designers, data scientists, and other cross-functional partners in a fast-paced environment.

Lead governance, risk, and compliance activities for AI/ML systems, LLM integrations, AI agents, and related vendors. Conduct AI risk and third-party assessments, map controls to frameworks, manage remediation, support audits, develop AI-specific policies, report risk metrics, monitor regulatory developments, and coordinate incident governance with Legal, Security, Product, and Engineering teams.

Leads end-to-end design of AI-first consumer product experiences, from research and problem framing through prototypes and polished interfaces. Translates complex AI insights into intuitive, trustworthy workflows; conducts user research and usability testing; and collaborates with product, engineering, and data science teams on production-ready solutions. Advocates for accessible, inclusive, ethical, and transparent AI design while using Figma and AI-enabled tools throughout the design process.

Lead the technical direction and execution of WHOOP’s foundation AI modeling efforts across wearable sensor data, language, biomarkers, and behavioral signals. Drive high-risk research from hypothesis to production, shape AI strategy and infrastructure decisions, collaborate across research, product, and engineering, mentor senior technical talent, establish evaluation standards, and represent WHOOP externally through recruiting, partnerships, and the machine learning research community.

Build and operate production AI systems powering WHOOP Coach, AI Support, and other intelligent product features. Lead AI/ML initiatives across data pipelines, dataset design, LLM fine-tuning, evaluation, deployment, experimentation, observability, and continuous feedback loops. Partner with product and data science to create reliable systems based on member needs and real-world usage. Mentor engineers and data scientists while establishing best practices for applied AI/ML, privacy, security, and production lifecycle management.