Top Artificial Intelligence Jobs

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, IT, and business leaders to deliver trusted, scalable reporting and decision-support capabilities. Manages BI demand, adoption, performance, standards, and team development while remaining technically involved in solution design and complex initiatives.

Manage data and AI project delivery across matrixed teams, including planning, execution, monitoring, risk management, stakeholder communication, and project closure. Establish program status reporting, executive dashboards, steering committee materials, demand intake, business cases, prioritization, PMO standards, resource tracking, change control, and contractor onboarding. Drive continuous improvement and ensure projects align with strategic priorities, capacity, budgets, safety, and customer objectives.

Drive technical sales engagements with healthcare organizations by conducting discovery, mapping workflows, delivering product demonstrations, responding to RFPs and RFIs, and designing tailored solutions. Advise sales teams and customers on EHR integrations, patient access workflows, revenue cycle processes, APIs, HL7, FHIR, and webhooks. Collaborate with product, marketing, and stakeholders to improve offerings and support go-to-market initiatives.

Leads AbbVie Operations’ enterprise AI and digital transformation strategy across supply chain, quality, product development, engineering, and security. Owns the multi-year digital roadmap, architecture standards, governance, investment planning, value realization, and scaled deployment of Industry 4.0/5.0 technologies. Builds executive partnerships, vendor ecosystems, digital capabilities, and high-performing teams while ensuring GxP compliance, data integrity, and cybersecurity across global manufacturing operations.

Leads the operation, governance, and expansion of AI and machine learning models for commercial forecasting across brands and geographies. Establishes modeling, validation, documentation, deployment, and monitoring standards; partners with forecasting, finance, technology, and business teams; explains model outputs to senior leaders; evaluates emerging AI methods; prioritizes modeling initiatives; and manages a team of forecasting data scientists.

Leads a team of data scientists operating, maintaining, and expanding AI/ML sales forecasting models. Builds forecasting models, monitors performance, delivers outputs for financial planning, explains results to stakeholders, documents model history, supports AI governance, and prioritizes new modeling opportunities. Partners across finance, technology, forecasting, and business teams while coaching team members and managing work plans.

Leads analytical teams supporting senior executives across operations, marketing, and product functions. Sets priorities, oversees complex business analyses, and applies data-driven insights to guide strategic decisions. Partners with P&L owners and business leaders to solve problems, align analytical resources, manage competing priorities, develop employees, and improve business intelligence capabilities. The role also includes people management, risk oversight, process optimization, resource allocation, and executive communication.

Conduct applied AI research focused on foundation models, LLM customization, and fine-tuning. Design, train, evaluate, validate, and deploy large-scale models using PyTorch, AWS, Hugging Face, and Lightning. Develop scalable research and platform code, reproduce and extend peer-reviewed work, design controlled experiments, publish findings, and collaborate with data scientists, engineers, and product managers to deliver AI-powered products.

Leads the vision, strategy, roadmap, architecture modernization, governance, and team growth for Capital One’s AI Assistance platform and Eno chatbot. Partners with product, engineering, data science, design, and risk teams to deliver customer-focused digital financial experiences, manage AI/ML risks, and achieve measurable business outcomes.

Leads data science for foundational AI and automation across a global payments network. Partners with data scientists, engineers, ML engineers, and product managers to develop scalable models and AI agents using PyTorch, AWS, vector databases, and LLMs. Serves as an NLP and LLM domain expert, translates technical work into business value, develops talent, and delivers production-scale libraries, platforms, and solutions.

Leads full-stack software engineering teams, technology portfolios, and large-scale cloud-native initiatives. Responsibilities include setting technical strategy, managing engineering talent, driving architectural and roadmap decisions, delivering distributed microservices and full-stack systems, and aligning engineering execution with enterprise goals. The role involves AWS and other cloud technologies, modern programming languages, databases, containers, Agile delivery, AI-enabled development, and regulatory technology solutions.

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, adoption, and AI-assisted analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable, secure, reusable BI capabilities. Manages and develops the BI team, prioritizes demand, measures business value, and guides technical design and delivery across Power BI, Snowflake, and related platforms.

Build, test, deploy, and productionalize secure AI and machine learning systems for internal tools, customer products, and operational workflows. The role involves generative AI, NLP, predictive modeling, responsible AI, model evaluation, monitoring, documentation, and collaboration with engineering, data, and business teams. Candidates should have strong Python and software engineering skills, experience with LLM applications and modern AI tooling, and familiarity with cloud platforms, privacy, security, and compliance.

Drive the product vision for Modular's cloud compute platform, collaborating with teams to enhance AI service capabilities and customer engagement.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, governance, delivery standards, and AI-assisted analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable Power BI and Snowflake capabilities. Manages BI demand, adoption, reliability, and business value while leading, coaching, and developing the BI team and remaining technically hands-on.

Own Kovo’s legal and compliance function as its sole attorney. Design low-obligation regulatory structures for new consumer financial products, manage licensing, bank partnerships, privacy, BSA/AML/KYC, fraud policy, marketing review, disputes, audits, and regulator relationships. Build scalable policies and agentic workflows that automate recurring work while maintaining rigorous legal judgment. Advise founders, product, engineering, marketing, and customer experience with clear, actionable guidance.

Lead product definition, technical strategy, customer discovery, and go-to-market execution for MCU-based server platform-management solutions. Define silicon, firmware, protocol, SDK, and reference-design requirements for distributed control across compute, accelerator, storage, power, and cooling systems. Engage hyperscalers, OEMs, ODMs, and ecosystem partners; evaluate standards and competitive solutions; create positioning, launch plans, business cases, roadmaps, and sales enablement. Coordinate architecture, engineering, applications, sales, and strategic customer teams through product development, interoperability validation, and customer design-ins.

Own the enterprise data and AI platform roadmap and architecture. Design and maintain dbt models, semantic layers, data quality tests, PostgreSQL infrastructure, and automated Prefect and GitHub Actions deployments. Manage cloud security, access controls, encryption, credentials, governance, and data standards. Build secure AI integrations and guide AI applications from prototype to production. Lead cross-functional technical decisions, direct engineering partners, and chair the Data Governance Committee.

Designs and maintains scalable backend services, APIs, event-driven microservices, databases, and reliable data pipelines using Java and Python. Builds AI/ML-powered features, including inference services, prompt orchestration, vector search, and ML pipelines. Ensures production readiness through CI/CD, automated testing, observability, monitoring, incident response, and secure coding. Collaborates with product, QA, SRE, data science, and stakeholders while mentoring engineers and leading technical design discussions.

Leads enterprise knowledge and AI transformation across Customer Success, Support, Enablement, Product, Operations, and Technology. Develops knowledge architecture, taxonomy, governance, metadata, content standards, ownership, and lifecycle processes. Builds AI-ready knowledge foundations for retrieval, self-service, copilots, and agentic workflows. Evaluates and implements AI opportunities, improves content and response quality using performance data, drives Knowledge-Centered Service practices, and leads cross-functional adoption and change without direct authority.

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, adoption, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, IT, and business leaders to deliver scalable, trusted reporting and decision-support capabilities. Manages and develops the BI team, prioritizes demand, establishes delivery standards and performance metrics, and remains hands-on in solution design and troubleshooting.

Develop and deploy AI solutions across the organization, integrate internal applications with AI agents and APIs, evaluate external AI technologies, and build scalable infrastructure. The role also provides access to AI tools, trains colleagues, identifies emerging use cases, and collaborates with software teams on practical AI adoption.

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable, secure, trusted reporting and self-service experiences. Manages BI demand prioritization, adoption metrics, stakeholder relationships, technical standards, and a BI team while remaining hands-on in solution design and troubleshooting.

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, adoption, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable Power BI and Snowflake capabilities. Manages BI demand, prioritization, standards, performance, security, stakeholder relationships, and team development while remaining technically hands-on.

Build infrastructure for AI-driven software development, including cloud coding environments, autonomous coding agents, SRE integrations, and reusable agent platforms. Own developer environments, agent integrations, security guardrails, observability, evaluation, and feedback loops. The role requires deep infrastructure experience across AWS, containers, infrastructure as code, CI/CD, and TypeScript/Node.js, plus hands-on use and orchestration of AI coding agents.