Top Artificial Intelligence Jobs

Leads major cross-department software initiatives from scoping through delivery, establishes technical roadmaps, evaluates technologies through proofs of concept, and guides strategic decisions. Oversees quality assurance, compliance, documentation, standards, and secure software delivery. Mentors teams, manages stakeholders and vendors, supports process improvement, and drives measurable productivity gains. Requires strong software engineering expertise, Java/Spring or Python coding, AWS, Databricks or Snowflake, and experience applying AI in software design.

Leads Mastercard’s Open Finance data science strategy, products, and global organization. Oversees production machine learning and AI capabilities for transaction categorization, entity extraction, fraud detection, credit risk, personalization, and predictive analytics. Partners with Product, Engineering, Sales, Risk, Marketing, Legal, and Compliance to commercialize scalable, explainable, and responsibly governed solutions. Builds talent, establishes operating standards, drives MLOps and model governance, and advises executives and customers on AI applications.

Leads development and delivery of Mastercard’s advertiser and commerce media products. Responsibilities include defining product concepts, requirements, roadmaps, MVPs, workflows, and technical features; partnering with Engineering, Data Science, design, sales, legal, privacy, and publisher teams; driving research, testing, GTM support, business cases, and stakeholder alignment; and mentoring junior product managers. The role focuses on adtech capabilities such as campaign automation, creative decisioning, offers optimization, audience building, and identity resolution.

Leads Mastercard’s global AI Engineering organization, overseeing the delivery and scaling of enterprise AI products, agentic AI solutions, reusable AI capabilities, and intelligent automation. Owns end-to-end engineering execution, production readiness, security, governance, reliability, adoption, and measurable business outcomes. Partners across technology, risk, security, product, and business teams while developing a high-performing global organization of AI engineering leaders and engineers.

Leads Mastercard’s global AI Engineering organization within the AI Center of Excellence. Oversees enterprise AI product delivery from design through production, scaling reusable AI assets, agentic solutions, automation, and shared capabilities. Ensures reliability, security, governance, compliance, and operational excellence in regulated environments. Partners cross-functionally to deliver measurable business outcomes and leads the development of global AI engineering leaders, architects, and engineers.

Own the AI roadmap for battery manufacturing, identifying, benchmarking, piloting, and scaling use cases that improve yield, quality, cost, and launch speed. Build proofs of concept and reference architectures for process optimization, defect vision, yield genealogy, and predictive maintenance. Establish reusable data, labeling, and model standards; evaluate vendors; guide engineering teams; align with IT and OT on security and scalability; and apply generative and agentic AI to plant workflows.

Partners with digital technology business leaders to align people strategies with business objectives. Advises on workforce planning, succession, organization design, change management, culture, leadership development, and team effectiveness. Coaches senior leaders, analyzes workforce data and trends, operationalizes talent initiatives, and collaborates with HR centers of excellence and People Operations to deliver effective solutions.

Own the operating rhythm for ServiceNow’s Talent Acquisition innovation portfolio. Manage emerging technology pilots from kickoff through results, coordinate RFIs, track milestones and workstreams, prepare status reporting, and communicate updates to leadership and the broader TA organization. The role also serves as the cybersecurity point person for administrative and fraud-management needs while partnering with AI, Product, Technology, and Cybersecurity teams.

Build AI agents and data acquisition systems, evaluate dataset quality, define quality KPIs, and improve data processes. Partner with product teams to deploy data into customer-facing products and acquire datasets from third parties, including coordinating vendors and contracts. The role requires organizing multiple projects, structuring analyses, communicating tradeoffs, and using data to support investment decisions and customer outcomes.

Own the vision, strategy, and roadmap for Braze’s Intelligence products, including AI-driven optimization, recommendations, and decisioning features. Partner with engineering and design to improve model quality, reliability, transparency, adoption, retention, and customer uplift. Lead product launches, competitive analysis, stakeholder communication, and go-to-market collaboration while connecting product decisions to revenue impact.

Own the vision, strategy, and roadmap for Braze’s Intelligence products, including AI-driven optimization, recommendations, and decisioning. Partner with engineering and design to improve model quality, reliability, adoption, customer uplift, and revenue impact. Build transparent, trustworthy AI experiences, monitor competitive trends, lead product launches, and coordinate with marketing, customer success, and other stakeholders.

Own the vision, strategy, roadmap, and success metrics for Braze’s AI and machine learning intelligence products. Partner with engineering and design to improve model quality, reliability, transparency, customer uplift, adoption, and retention. Lead launches with product marketing, customer success, and other go-to-market teams while managing stakeholders and communicating decisions. The role requires translating complex algorithms into trustworthy marketer experiences and monitoring the competitive marketing AI landscape.

Own the vision, strategy, and roadmap for Braze’s Intelligence products, including AI-powered optimization, recommendations, and decisioning. Partner with engineering and design to improve model quality, reliability, customer uplift, adoption, and retention. Define success metrics, make AI transparent and trustworthy, monitor competitive trends, lead product launches, and align internal and external stakeholders. The role requires strong product judgment, communication, cross-functional leadership, and experience translating complex algorithms into simple marketer experiences.

Leads business continuity, crisis response, operational resilience, and third-party risk management across banking and premium products. Directs incident command, disaster recovery frameworks, vendor risk oversight, continuity planning, post-incident remediation, regulatory engagement, and technology resilience initiatives. Partners with technology risk, supplier management, audit, regulators, and senior business leaders to protect critical services and customer trust amid evolving technology and AI-driven risks.

Leads process management and operational improvement initiatives across Network Risk Operations. Partners with stakeholders to identify business needs, analyze trends and risks, and implement solutions involving process changes, dashboards, digital tools, automation, AI, and enablement. Establishes governance, prioritization, and controls while driving scalable solutions, stakeholder alignment, adoption, and measurable improvements across cross-functional teams.

Provides cybersecurity consulting and governance for a business function, evaluating architectures, infrastructure, cloud, network, data, access, and resilience risks. Advises engineering and product teams on security capabilities, risk mitigation, and secure development. Manages cyber risks, supports incident analysis, presents security health to executives, and evaluates AI-related security, privacy, compliance, and attack risks.

Develop and improve reliable LLM and deep learning capabilities, build scalable real-time machine learning models, advance Responsible AI practices, and define technical strategies for deep learning, RAG, and LLMs. Collaborate with AI scientists and engineers, conduct ML and reinforcement learning research, fine-tune models, and drive adoption of AI best practices across service teams.

Leads complex AI strategy and solution-delivery engagements for pharmaceutical, biotechnology, and medical technology clients. Serves as the primary client advisor, translating scientific, operational, technical, and regulatory needs into scalable solution designs and implementation plans. Manages governance, workstreams, risks, resources, and executive reporting while guiding multidisciplinary teams. Develops reusable AI delivery methods, reference architectures, playbooks, and enterprise offerings, incorporating privacy, cybersecurity, model risk, validation, GxP, and responsible AI considerations.

Lead the technical and product direction for a production conversational AI customer agent. Build and scale agentic systems covering orchestration, evaluation, guardrails, memory, context, reliability, and failure handling. Remain hands-on with coding, architecture, debugging, and production operations while mentoring engineers and partnering with product, design, data science, and go-to-market teams. The role is based in-office in Boston and may require up to 10% travel.

Lead the technical and product direction for a production conversational AI customer agent. Build and scale agentic systems involving orchestration, evaluation, guardrails, memory, context, reliability, and failure handling. Write and review code, make architecture decisions, collaborate cross-functionally, mentor engineers, evaluate emerging AI technologies, and support systems through launch and live customer usage.

Develop and execute indirect procurement category strategies for capital equipment, operational equipment, and complex services. Lead strategic sourcing, RFx initiatives, cost reduction, should-cost analysis, contract negotiations, supplier relationship management, and performance improvement. Partner with Legal, Global Procurement, executives, and cross-functional stakeholders while managing commercial and operational issues. The role requires data-driven recommendations, multiple concurrent sourcing projects, and 15% domestic travel.

Develops and implements environmental compliance and sustainability programs. Responsibilities include hazardous and solid waste management, chemical approvals, stormwater compliance, contractor oversight, regulatory reporting, environmental data analysis, audits, corrective actions, and regulatory inspections. The role also uses AI and digital tools to identify compliance risks and automate EHS workflows while supporting construction and operational environmental requirements.

Manage full-cycle technical recruiting for Engineering, Product, Security, UX, and R&D roles. Partner with hiring leaders on role definition, structured interviews, sourcing strategy, market research, candidate assessment, pipeline management, and offer negotiations. Build diverse talent pipelines, use recruiting data to guide decisions, maintain accurate Greenhouse documentation, deliver an inclusive candidate experience, and improve recruiting practices through responsible AI use and shared resources.

Manage full-cycle recruiting for go-to-market roles across sales, marketing, customer success, professional services, and related teams. Partner with hiring leaders, build diverse talent pipelines, conduct structured assessments, use market and funnel data to guide hiring, manage candidate experiences, negotiate offers, and maintain recruiting documentation. The role also involves improving recruiting practices, responsibly using AI, and advising stakeholders in a globally distributed, remote-first environment.

Leads Bedrock’s enterprise data, analytics, and AI strategy, roadmap, governance, platforms, integrations, reporting, and automation. Oversees technical teams, evaluates and implements Microsoft data platforms, translates business needs into solutions, manages AI programs, and establishes data quality, security, compliance, adoption, and performance standards across the organization.