Top Artificial Intelligence Jobs

Leads AI technology integration and deployment within the tax practice. Oversees data infrastructure, pipelines, modeling, quality validation, and multi-source integration. Develops Python-based analytics solutions using machine learning and natural language processing, conducts rapid experimentation, and drives data-informed innovation. Coaches and develops high-performing teams while collaborating with stakeholders and advising on strategic initiatives.

The Founding Business Development Representative will create and execute Credal’s outbound strategy, including personalized emails, cold calls, warm introductions, and campaigns. The role involves initiating conversations with technical leaders and executives, qualifying prospects, understanding pain points, sharing market feedback with product teams, and building the company’s outbound playbook. This in-person NYC position offers potential progression into account executive, growth, or customer-facing leadership roles.

Lead global executive recruiting from strategy through offer closure. Partner with hiring managers, advise senior leadership, mentor recruiters, build executive talent networks, manage search firms, and deliver a strong candidate experience. The role requires extensive in-house executive hiring expertise, strategic judgment, global collaboration, and the ability to identify and secure senior leaders in a fast-paced environment.

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.

Lead creative strategy for paid social campaigns by turning audience insights, performance data, and cultural trends into high-performing creative. Build briefs, testing frameworks, and a centralized learnings library; partner cross-functionally and with agencies; run strategy sessions; and adopt emerging technologies, including AI, to improve ideation and optimization.

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 enablement programs by coordinating engineering, product, legal, security, privacy, and business stakeholders. Manages AI initiative intake, prioritization, implementation playbooks, pilot deployments, compliance reviews, and executive reporting. Facilitates agile action teams, tracks complex workflows and risks, and maintains dashboards showing milestones, timelines, and mitigation strategies.

Leads a portfolio of high-priority, cross-functional initiatives supporting Mastercard’s integration with Recorded Future and long-term growth. Responsibilities include shaping strategy, building roadmaps and operating models, coordinating Product, Strategy, Sales, Marketing, Finance, Legal, Engineering, and other teams, facilitating executive decisions, managing risks and dependencies, preparing leadership updates, and transitioning initiatives to permanent business owners.

Lead AI- and data-driven business transformations for Life Sciences customers using the Celonis Platform. Own value realization from discovery through ROI, manage executive stakeholders, facilitate business value workshops, and oversee global transformation programs. Develop account strategies, CoE roadmaps, adoption plans, and AI-assisted project management processes while partnering with sales and technical teams. Apply expertise across supply chain, finance, commercial, and clinical R&D domains to deliver measurable process improvements.

Leads strategic technical engagement with managed partners, combining pre-sales solution consulting, business development, architecture, and AI adoption. Responsibilities include joint business planning, practice growth, solution strategy, technical discovery, demonstrations, proofs of concept, escalations, executive briefings, and commercialization. The role translates ServiceNow and AI capabilities into scalable partner solutions, influences pipeline, improves competitive win rates, and coordinates internal technical and specialist teams.

Develops practice-specific architectures, reusable solution assets, proofs of concept, training, and executive briefings with ServiceNow partners. Provides senior technical expertise across risk and security, guides competitive positioning, mentors partner architects and presales teams, assesses capability gaps, and supports solution commercialization. Collaborates with product, engineering, sales consulting, and partner management teams to improve partner maturity, pipeline influence, self-sufficiency, and competitive win rates.

Build and deploy quantitative risk models, pricing libraries, margin replication tools, and real-time monitoring systems for futures markets. Integrate AI and machine learning for predictive risk modeling, anomaly detection, and trading surveillance. Support live trading, investigate incidents, analyze market behavior, and implement systemic fixes. Collaborate with traders and engineering teams, guide risk-tech architecture, and mentor junior staff. Coverage during Asian market hours may include early mornings or overnight shifts.

Leads enterprise data-domain architecture strategy across products, applications, and technologies. Establishes governance, reusable frameworks, architectural standards, and portfolio guardrails while evaluating emerging technologies and AI capabilities. Advises leadership on target-state architecture, promotes hybrid and multi-cloud adoption, reduces tooling duplication, and improves traceability, resilience, security, cost performance, and operational governance. Requires deep expertise in data management architecture, databases, ETL, data platforms, analytics, mining, and data governance, along with extensive cloud-native experience.

Leads international CRM decision intelligence, translating customer, campaign, and market data into strategy and next-best-action recommendations. Oversees predictive analytics, segmentation, measurement, dashboards, data quality, privacy, opportunity sizing, and AI-enabled insight generation across global markets. Partners with CRM, data, AI, digital, commercial, legal, and compliance teams to scale trustworthy personalization and analytics.

Leads product strategy and strategic initiatives for Capital One’s Consumer and Developer Experience organization. Partners with senior leaders, analyzes business landscapes, drives annual planning, supports AI transformation, develops product innovation and prototypes with engineering, and leads strategy and product teams. The role requires strong strategic problem-solving, product orientation, analytics, people leadership, relationship-building, communication, and the ability to operate effectively in ambiguity.

Support Consumer and Developer Experience leadership by solving strategic business questions, leading initiatives such as AI transformation, conducting analytics and market assessments, shaping long-term product innovation, and partnering with engineering on prototypes. The role also builds stakeholder relationships, develops strategic capabilities, promotes AI-enabled efficiency, and contributes to annual planning and organizational alignment.

Leads analytics, business intelligence, strategic planning, AI transformation, organizational transformation, and product innovation for Capital One’s Consumer and Developer Experience organization. Partners with senior leaders, engineering, and product teams to address complex strategic questions, develop prototypes, align priorities, and drive scalable digital experiences. Manages and develops strategy and product teams while fostering customer-centric culture, cross-functional collaboration, and AI adoption.

Lead enterprise portfolio strategy and delivery for EPTech Top of House: translate executive vision into roadmaps, automate portfolio processes with AI, manage intake/capacity and governance, mitigate technology risk, drive OKR reviews and PI planning, and influence senior stakeholders to align execution with business intent.

Leads product strategy and execution for an AI-powered Lead Intelligence data pipeline serving Business Cards and Payments. Partners with Engineering, Data Science, Field Analytics, Sales, and Marketing to unify, enrich, verify, and continuously refresh business sales leads. Transforms fragmented, manual prospecting processes into targeted lead queues with actionable prospect context for relationship managers and digital channels.

Owns the strategy, backlog, requirements, and delivery of AI-powered conversational assistants and proactive outbound engagement solutions. Collaborates with engineering, data science, architecture, and business teams to define technical specifications, model criteria, testing strategies, and product metrics. Evaluates emerging AI and contact center technologies, manages Agile workflows, and drives continuous product improvement across digital consumer experiences.

Leads product vision, roadmaps, prioritization, and delivery for enterprise data science enablement capabilities. Serves as Product Owner, translating customer and stakeholder needs into backlogs and technical solutions. Partners with data scientists, engineers, architects, and business teams to support AI/ML development, deployment, monitoring, adoption, and business value realization. Drives reusable platform capabilities, technical debt reduction, DevOps and MLOps improvements, Agile delivery, and executive communication.

Own the vision, roadmap, investment decisions, and lifecycle of enterprise data and analytics products. Lead discovery, requirements, delivery, backlog management, adoption, stakeholder alignment, and continuous improvement across data platforms, governed data products, AI, and BI solutions. Partner with engineering, data science, business, and executive teams while managing risks, budgets, vendors, KPIs, and multi-year initiatives.