Top Artificial Intelligence Jobs

Owns the Trade and Working Capital AI use-case portfolio from ideation through delivery and value realization. Translates business needs into technical requirements, prioritizes opportunities, coordinates with AI, data science, technology, data, and infrastructure teams, and drives adoption across product, commercial, and productivity applications. The role also leads AI literacy initiatives, aligns business priorities with enterprise governance and AI programs, manages multi-workstream delivery, and reports progress and realized value to senior stakeholders.

Leads strategic technical engagement with global and regional partners, combining pre-sales solution consulting, architecture, business development, AI adoption, and co-innovation. Responsibilities include technical discovery, executive briefings, demonstrations, proof-of-concept leadership, solution strategy, partner business planning, practice growth, value engineering, and technical escalation support. The role requires strong ServiceNow workflow expertise, executive influence, partner ecosystem experience, and the ability to create scalable, AI-enabled enterprise solutions.

Leads architecture and software engineering for cloud-based applications within JPMorgan Chase’s CTO-IAM organization. Defines target-state architecture, evaluates emerging technologies and vendors, develops and reviews secure production code, troubleshoots systems, and improves operational stability. Establishes reusable AI-enabled engineering patterns and governance across SDLC and CI/CD practices while ensuring resiliency, security, traceability, and auditability.

Leads AWS cloud architecture and site reliability engineering for business-critical production services. Responsibilities include production readiness, incident response, observability, SLI/SLO and error-budget management, capacity planning, resiliency, disaster recovery, infrastructure automation, cloud cost optimization, and major incident remediation. The role also establishes operational standards, advances responsible AI-assisted engineering practices, and communicates complex technical strategies to leadership in a regulated financial-services environment.

Owns Genius AI’s webinar program and national trade show initiatives from planning through execution and performance analysis. Responsibilities include managing topics, talent, promotion, budgets, vendors, activation concepts, lead routing, sales partnerships, pipeline results, and AI-powered workflow automation. The role also develops new event formats, monitors performance metrics, and travels domestically 1–3 times monthly while working primarily in person from the NYC headquarters.

Leads enterprise competitive intelligence capabilities, including data collection, matching, scraping, governance, quality standards, analytical methodologies, and AI-enabled workflows. Partners with Product, Engineering, Data Science, Merchandising, Pricing, Digital, Marketplace, and Strategy teams to translate business needs into scalable solutions. Develops metrics, models, validation processes, and insights that support business decisions, while potentially managing and developing a small analytics team.

Leads complex, cross-functional technology initiatives from planning through delivery. Manages milestones, dependencies, risks, change control, stakeholder alignment, executive reporting, documentation, production readiness, and continuous improvement. Partners with product and engineering teams on modernization and enterprise technology programs while using AI-assisted workflows with appropriate validation and data-sensitivity controls.

Drives revenue growth across advertiser and agency accounts in assigned industry verticals. Responsibilities include prospecting, account planning, consultative selling, solution design, proposals, negotiations, closing, forecasting, and client retention. The role develops cross-platform advertising solutions using audience insights, attribution, measurement, and data-driven strategy; presents to executives; coordinates with internal teams; and contributes to go-to-market strategies, pipeline reporting, and account performance management.

Own the full B2B software sales cycle, including prospecting, discovery, demos, business cases, negotiation, closing, and account expansion. Build pipeline through outbound, referrals, partners, conferences, and relationships. Sell to owners, executives, and operators by demonstrating measurable ROI. Collaborate with the CEO on deals and territory strategy, work with engineering on customer feedback, and operate independently while helping improve the sales organization.

Develops and scales generative AI and automation solutions for memory circuit design, layout, verification, simulation, and tapeout workflows. Uses engineering and silicon data for predictive insights and optimization of floorplanning, placement, routing, and validation. Collaborates with design, CAD, product, manufacturing, and process teams to reduce manual effort, improve quality, and accelerate time-to-tapeout. Requires production-quality Python development and experience applying machine learning, data analysis, or automation to engineering workflows.

Designs and leads enterprise AI architectures from proof of concept through production, including data ingestion, model training, LLM/RAG pipelines, agentic workflows, deployment, monitoring, and lifecycle management. Evaluates AI technologies, establishes strategy and standards, develops low-code and no-code automation layers, builds MVPs, and coordinates with executive, data science, IT, service tower, vendor, and consulting stakeholders. The hybrid role requires up to 20% domestic travel and U.S. Person status for export-control compliance.

Leads venture investment sourcing, evaluation, diligence, and execution across Seed through Series B. Drives company-wide AI and machine learning initiatives, maintains portfolio relationships, and develops executive, Board, and Investment Committee recommendations. The role requires technical fluency in AI or semiconductors, financial acumen, senior stakeholder influence, strategic judgment, team mentorship, and the ability to operate effectively in ambiguous, fast-paced environments.

Clean, repair, troubleshoot, rebuild, and test semiconductor equipment subassemblies. Maintain accurate equipment-tracking records, develop technical procedures, perform failure analysis, and prepare reports for underperforming subassemblies. Follow safety requirements, including PPE, lockout/tagout, and chemical safety protocols, while using AI to improve execution speed.

Owns major product roadmap components and strategic initiatives for software applications. Defines product outcomes, writes epics, features, and user stories, partners with engineering and UX, leads Agile delivery, coordinates client support, manages release plans, develops training and support materials, and applies user acceptance testing and AI/ML workflow knowledge.

Lead integration of autonomy components into reference implementations and deployable stacks. Develop C++ and Python tooling, software-in-the-loop and hardware-in-the-loop tests, platform integration layers, automated fixtures, and troubleshooting workflows. Investigate cross-system failures, support deployment to representative hardware, collaborate on flight testing, analyze integration issues, and create documentation and training materials. The role spans perception, localization, planning, real-time systems, and safety-critical autonomous platforms.

Advise clients on privacy, data protection, and responsible AI requirements. Evaluate AI systems for fairness, transparency, safety, privacy, accountability, and third-party risk. Develop governance operating models, policies, risk-tiering approaches, controls, impact assessments, and client deliverables. Interpret regulatory changes, support breach investigations, collaborate with legal, compliance, cybersecurity, data, and technology teams, and mentor junior staff. Apply technical literacy in AI/ML, GenAI, software development, technical architecture, and Python.

Supports financial crimes consulting engagements through research, data gathering, transaction and control analysis, regulatory risk assessment, and project coordination. Uses data analytics and AI tools to organize findings and prepare draft deliverables, presentations, status updates, and client discussion materials. Collaborates with project teams, tracks deliverables, reviews case documentation, and applies feedback while developing financial crimes compliance, risk management, and advisory skills.

Supports the transformation of enterprise Sales and Operations Planning by designing planning processes, scenario models, constraints, metrics, and decision rules. Partners with Sales, Supply Chain, Manufacturing, Product, Finance, IT, and vendors to implement an S&OP platform, define requirements, test system capabilities, align data, and evaluate scenarios. Develops analytics, reporting, and executive-ready insights to improve demand and supply planning, schedule stability, automation, and decision-making.

Leads Card customer analytics and AI strategy, overseeing analytics leaders, data scientists, and analysts. Drives GenAI, machine learning, experimentation, personalization, competitive intelligence, and forward-looking analysis across product, pricing, marketing, and servicing. Partners with business and technical stakeholders to deliver responsible solutions from concept through production, while building organizational capabilities, developing talent, and influencing executive decisions.

Lead complex security incident investigations from assessment through recovery, coordinating containment, remediation, evidence preservation, and stakeholder communication. Analyze threats across endpoint, identity, cloud, SaaS, network, and application environments. Build code, queries, automation, and AI-assisted workflows to improve evidence collection, detection, case management, and response. Lead post-incident reviews, drive lasting improvements, mentor responders, and participate in the incident response on-call rotation.

Own strategic technology partnerships from identification and business-case development through technical scoping, contract negotiation, integration, and go-to-market launch. Collaborate with Product, Engineering, Legal, Finance, Marketing, Sales, and executive stakeholders to align priorities, evaluate technical fit, close complex agreements, and deliver platform adoption. The role requires technical fluency across cybersecurity, cloud infrastructure, networking, developer platforms, or AI.

Leads AI strategy, teams, and production-scale machine learning initiatives. Responsibilities include establishing MLOps practices, integrating AI technologies, guiding build-versus-buy decisions, delivering intelligent solutions, implementing governance and responsible AI, and driving adoption across products and enterprise platforms. The role requires cross-functional leadership, technical expertise in machine learning and advanced AI methods, stakeholder influence, mentoring, and delivery of measurable business outcomes.

Leads multiple product squads across experience delivery, owning team direction, staffing, delivery quality, evidence-based discovery, launch readiness, and post-launch outcomes. Manages hiring, coaching, performance, capacity, and development of individual contributors into leaders. Partners with Product Strategy, Engineering, Design, Platform, and Marketing while maintaining craft standards, acceptance criteria, instrumentation, and responsible AI practices.

Leads data ownership and governance for data products, defining metadata, quality, controls, integration, and risk mitigation. Partners with business, analytics, technology, and engineering teams to deliver curated datasets and production-ready solutions. Uses advanced SQL for validation and root-cause analysis, manages workstreams and staff, and supports analytics and machine learning use cases. Applies AI and LLM tooling to automate governance activities and maintains data integrity across regulated environments.

Leads marketing data and analytics initiatives that improve audience targeting, campaign execution, measurement, and operational reliability. Translates business objectives into technical requirements, designs data and audience management approaches, develops quality monitoring and reporting, manages issue resolution, and partners with Product and Technology on platform enhancements. The role also identifies responsible AI applications, establishes governance and controls, and supports measurable, repeatable delivery across digital marketing channels.