Top Artificial Intelligence Jobs

Defines the technology vision and enterprise architecture strategy for Citi’s Trade Finance platforms. The role designs high-volume processing solutions, guides cloud, PaaS, and AI-native modernization, evaluates vendors, influences product roadmaps, and partners with senior stakeholders. It also strengthens cybersecurity controls for digital assets, manages architecture-related risk, and drives future-state technology strategies across business, product, operations, and technology teams.

Leads development of full-stack, cloud-native software using Java, Python, and AWS. Builds secure microservices, APIs, and LLM-powered capabilities; establishes engineering, testing, reliability, observability, and CI/CD standards; mentors engineers; drives responsible AI-assisted development; and manages production operations, incident response, and technical direction across agile initiatives.

Lead end-to-end delivery of cloud-native, full-stack software initiatives, defining architecture, engineering standards, reliability practices, observability, CI/CD, and secure production operations. Build microservices, APIs, and AI capabilities using LLMs and generative AI. Guide responsible AI-assisted development, lead incident response and continuous improvement, mentor engineers, and align technical priorities across stakeholders and initiatives.

Lead a globally distributed team building Zscaler’s enterprise data and AI platform. Own Snowflake, dbt, Matillion, data pipelines, knowledge graphs, vector stores, RAG systems, agentic operations, and production AI infrastructure. Translate platform strategy into roadmaps, operate the platform as an internal product, establish quality and observability standards, and provide hands-on technical and people leadership across architecture, engineering execution, hiring, mentoring, and delivery.

Owns the architecture of Caterpillar’s reinforcement learning systems for physical AI and autonomous construction equipment. Designs simulation-based training, imitation learning, foundation-model post-training, sim-to-real transfer, policy evaluation, safety, and deployment methodologies. Establishes standards for reproducibility, experimentation, benchmarks, and field performance while guiding cross-functional teams and translating research into reliable, production-ready learning systems.

Leads analytics and AI strategy, delivery, governance, and platform ownership for internal auditing. Manages data scientists, develops Power BI and Snowflake solutions, oversees reporting and control monitoring, and drives automation and AI adoption. Partners with audit and business leaders to translate requirements into scalable insights, improve decision-making, and establish secure, reliable analytics practices. The role also manages stakeholder relationships, vendor partnerships, team development, and analytics transformation initiatives.

Drives business transformation and strategic change initiatives by developing transformation strategies, improving processes and organizational design, managing change adoption, engaging senior stakeholders, coordinating cross-functional projects, delivering training, and tracking benefits realization. The role manages transformation projects from planning through post-implementation review while ensuring alignment with business objectives, timely delivery, budget adherence, and successful organizational adoption.

Coordinates a small team of research scientists, balancing rapidly changing research priorities, strategic direction, external deadlines, deliverables, and stakeholder tradeoffs. The role requires high-stakes judgment, negotiation, communication, empathy, and execution under uncertainty. It partners closely with executive leadership to influence frontier AI research strategy and ensure ambitious work is delivered with quality and timeliness.

Provides hands-on technical leadership for enterprise Data Trust platforms. Designs and operates distributed systems supporting data contracts, metadata, lineage, quality, privacy, access controls, reliability, and semantic context for analytics and AI. Leads batch and streaming capabilities across Snowflake, AWS, and Kafka; establishes observability, SLOs, automated enforcement, and operational rigor. Drives cross-functional architecture and multi-quarter initiatives while mentoring engineers and building reusable platform standards.

Leads the agentic AI roadmap for Azure Supportability, aligning engineering, product, and support teams on goals, requirements, milestones, and stakeholder communications. Conducts customer and competitive research, measures AI adoption and impact, identifies technical challenges, and iterates solutions using data-driven insights. The role requires significant experience in technical program management, AI or ML solution development, and cloud platforms.

Lead a team of 4–8 AI engineers while remaining hands-on with architecture, code reviews, debugging, and technical decisions. Own delivery of production AI systems, including LLM applications, agentic workflows, document extraction, ETL pipelines, observability, evaluation, and monitoring. Partner with product, platform, data engineering, recruiting, and customers to build reliable, scalable AI features and grow engineering talent.

Leads Intuitive’s global indirect procurement function, setting its vision, operating model, talent strategy, and multi-year roadmap. Owns global category management, strategic sourcing, supplier relationships, negotiations, risk management, source-to-pay optimization, compliance, and procurement technology. Partners with executives and cross-functional leaders to deliver measurable value, improve stakeholder experience, increase spend under management, and manage global travel and event services.

Own the vision, strategy, and roadmap for role-based experiences and extensibility within ServiceNow’s AI/Super Intelligence Control Tower. Define persona-specific workflows, upgrade-safe customization, information architecture, accessibility, localization, and UI framework partnerships. Collaborate across product, design, engineering, and business units to deliver coherent enterprise experiences. The role requires extensive product management experience, enterprise SaaS expertise, platform extensibility knowledge, AI familiarity, and strong cross-functional influence.

Own and build an entire product category or department while working directly with the CEO. Responsibilities span strategy, operations, sourcing, growth, finance, forecasting, unit economics, and AI-enabled automation. The role requires turning ambiguous business problems into structured decisions and execution, building internal systems and workflows, coordinating suppliers, and improving fulfillment and customer experience. This onsite position is intended for an ambitious operator with at least three years of experience and strong analytical, commercial, and technical fluency.

Designs and deploys AI-powered features and scalable AI/ML services across SaaS products. Responsibilities include translating business problems into AI solutions, integrating large language models, preparing data, evaluating model performance, writing Python, building secure deployment infrastructure, and collaborating with product, data, and cloud operations teams. The role requires production AI/ML experience, scalable data infrastructure expertise, AWS familiarity, and modern DevOps practices.

Supports the President and senior leadership through executive administration and complex project management. Responsibilities include coordinating strategic planning, tracking KPIs and project outcomes, overseeing managers and deliverables, conducting organizational analyses, improving processes and information systems, managing regulatory requirements, preparing communications, scheduling meetings, and coordinating special events. The role requires extensive healthcare and executive-support experience, strong Microsoft Office skills, discretion, communication ability, and occasional travel between sites.

Leads development of secure, scalable, cloud-native microservices applications for banking payments. Designs, builds, tests, debugs, and reviews production software using Java, React, distributed systems, and modern architectural patterns. Drives automation, resiliency, continuous delivery, technology modernization, and engineering best practices while mentoring colleagues and contributing to cross-team communities of practice.

Leads software engineering and quantitative development for asset management technology, building secure, scalable systems supporting research, portfolio management, and investment workflows. Develops and reviews production code using Java and/or Python, applies AWS cloud-native practices and infrastructure as code, improves operational stability, and promotes responsible AI-assisted engineering. Partners with stakeholders and vendors on architecture and technical solutions while supporting data engineering, distributed processing, databases, and financial services applications.

Designs and deploys enterprise AI systems centered on large language models, including fine-tuning, retrieval-augmented generation, prompt engineering, autonomous agents, and NLP applications. The role integrates AI into internal tools and digital products, evaluates frameworks, builds scalable training and deployment pipelines, leads architecture decisions, applies emerging research, and mentors team members.

Leads cybersecurity solution sales for enterprise and small-to-medium business customers. Builds security transformation strategies, identifies and qualifies opportunities, develops pipelines, conducts consultative conversations, and drives complex cloud solution deals through closure. Partners with internal teams and channel partners on proposals, account planning, forecasting, competitive strategy, events, and customer outcomes. Serves as a cybersecurity subject matter expert, mentors colleagues, and supports customer adoption of AI, cloud, and security solutions.

Develop and operate autonomous AI agents and enterprise integrations using Databricks, Claude, MCP, and event-driven architectures. Build Databricks Apps, maintain MCP connectors, monitor agent performance, manage incidents, and document workflows, triggers, dependencies, and data sources. Partner with business, governance, and process teams to identify suitable agentic AI applications, particularly for go-to-market systems, while applying logging, auditing, naming, and change-management standards.

Lead Applecart’s internal AI adoption and governance strategy. Own the AI tools roadmap, data classification standards, usage guardrails, client confidentiality protections, incident response, and adoption reporting. Partner with Legal, Security, IT, Engineering, and business leaders to evaluate vendors, launch pilots, define success criteria, train employees, and build use-case libraries. The role combines strategic judgment, technical risk management, governance implementation, and organizational enablement in a high-confidentiality environment.

Build and manage relationships with AI safety organizations, policy groups, funders, and political allies. Translate partner needs into polling, survey, and message-testing research questions; coordinate AI client projects from scoping through delivery; track requests, commitments, timelines, and priorities; review research materials; brief technical and political audiences; and help shape the firm’s AI research agenda.

Develop and evolve Thinking Machines’ visual brand across websites, launches, publications, and physical objects. Design, build, and improve digital experiences using code, while creating reusable tools, artwork generators, data-driven charts, and publishing components. Collaborate with illustrators, animators, graphic designers, engineers, and researchers to turn concepts into polished, accessible work. Contribute original ideas, manage open-ended projects, incorporate feedback, and explore agentic workflows and emerging technology.

Lead brightwheel’s education business from early traction through product-market fit and scale. Own product vision, customer discovery, prototyping, pricing, business economics, and growth across educators, families, states, districts, and early education programs. Build hands-on with AI and modern tools, partner with the CEO and executive team, recruit and develop the team, and drive outcomes visible to the board.