Top Artificial Intelligence Jobs

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 reporting and decision-support capabilities. Manages and develops the BI team, prioritizes demand, establishes delivery standards, measures business value, and remains hands-on in solution design and technical problem-solving.

Provides high-level administrative and operational support to the Chief Data and AI Officer and organization. Responsibilities include executive calendar and travel management, meeting and event coordination, correspondence and presentation preparation, vendor and expense administration, purchase order and budget tracking, onboarding logistics, confidential information handling, and cross-functional coordination. The role also improves administrative processes and uses AI tools to enhance productivity.

Lead and grow a full-stack engineering team building AI-powered Windows experiences, including agentic and autopilot capabilities. Responsibilities include planning and prioritizing projects, contributing to code and infrastructure, guiding architecture and design, meeting security and compliance requirements, coordinating cross-team dependencies, and delivering features used by millions of people.

Develop production software for AI-driven semiconductor equipment diagnostics, monitoring, predictive maintenance, and automation. Build agentic AI frameworks integrating LLMs with equipment data, telemetry, hardware systems, streaming platforms, databases, and knowledge systems. Create APIs, data pipelines, orchestration layers, and web applications for troubleshooting and intelligent workflows. Collaborate with multidisciplinary engineering teams and deploy secure solutions in global semiconductor manufacturing environments.

Leads technical presales, customer discovery, proofs of concept, and implementation for Gracenote’s API and AI products. Designs and deploys focused AI agents using MCP servers and agentic frameworks, advises customers on enterprise integrations, provides code-level guidance, validates new tools, and influences product roadmaps. Requires strong experience with Python or TypeScript, LLM orchestration, cloud AI platforms, enterprise security, and stakeholder engagement. Travel to customer sites globally may reach 40%.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, governance, delivery standards, and AI-enabled analytics experiences. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable Power BI and Snowflake capabilities. Manages BI demand, adoption, performance, and business value while leading, coaching, and developing the BI team and broader analytics community.

Build and maintain Life360’s iOS advertising SDK, mediation and header-bidding integrations, ad formats, privacy and consent flows, instrumentation, and experimentation systems. Improve ad quality, performance, and reliability at large scale while collaborating with ad operations, data, product, and external partners. Use AI-native workflows with agentic coding tools, contribute to architecture and incident response, and mentor teammates.

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, and adoption. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable Power BI and Snowflake capabilities, self-service analytics, and AI-assisted insights. Manages BI demand prioritization, stakeholder relationships, performance measurement, and a BI team while maintaining sufficient technical involvement to guide architecture, troubleshoot issues, and support priority initiatives.

Leads strategic enterprise engagements to identify high-value AI and Microsoft 365 Copilot use cases, deliver technical demonstrations and proofs of concept, quantify business value, and accelerate customer adoption. Provides technical sales strategy, competitive positioning, executive guidance, and coaching to sales teams. Partners with Microsoft engineering, marketing, and external partners to resolve technical barriers, scale successful sales motions, and influence product direction through customer feedback.

Leads development of BMS’s commercial AI product context and knowledge layer. Translates business knowledge into knowledge graphs, semantic models, and reusable AI assets; executes product roadmaps; oversees ML operations and AI performance evaluation; designs golden Q&A testing frameworks; supports UAT, governance, privacy, and responsible AI controls; and partners with brand, IT, analytics, offshore, and vendor teams to improve AI-driven commercial decision-making.

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 reporting and decision-support capabilities. Manages and develops the BI team, prioritizes demand, establishes delivery standards, measures business value, and remains hands-on in solution design and complex issue resolution.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, governance, delivery standards, and AI-enabled analytics. Manages the BI team, partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT, and translates business needs into scalable BI products. Oversees adoption, reliability, performance, security, and business value while coaching technical professionals and remaining involved in solution design and troubleshooting.

Leads the multi-year strategy and roadmap for enterprise data platform and AI/ML products, including lakehouse, governance, BI, MLOps, LLMOps, RAG, and multi-agent systems. Partners with senior engineering and executive stakeholders, prioritizes portfolios, oversees responsible AI and regulatory compliance, manages backlogs and KPIs, and leads Product Managers and Business Analysts across multiple engineering squads.

Leads the discovery, design, prototyping, governance, implementation, and scaling of AI and automation solutions across engineering, project delivery, and corporate operations. Builds an enterprise AI roadmap, translates business needs into requirements, coordinates cross-functional delivery, supports responsible AI practices, and drives employee adoption through training, communications, reusable standards, and communities of practice.

Leads technical sales engagements for Microsoft cloud and AI solutions. Delivers demonstrations, proofs of concept, hackathons, coding sessions, and architecture workshops to drive customer adoption and production deployment. Designs secure, scalable, cloud-native and AI-enabled architectures; resolves technical blockers; collaborates with engineering teams; and advises customers on AI Foundry, Azure AI, agentic AI, Responsible AI, application modernization, and deployment workflows.

Build and deploy production AI, generative AI, machine learning, data engineering, and advanced analytics solutions for a regulated bank. Develop Snowflake-centered pipelines and Azure integrations, implement LLM, RAG, agent, and automation capabilities, and establish testing, monitoring, documentation, governance, security, and responsible AI practices. Partner with business, technology, risk, compliance, and legal teams to identify valuable use cases, evaluate emerging technologies, and scale reliable AI capabilities.

Own the architecture and technical direction of large-scale AI model training infrastructure. Build distributed training platforms and production services, extend open-source frameworks, resolve complex reliability issues, meet security and compliance requirements, and partner with researchers and product teams. Lead multi-quarter initiatives, mentor engineers, guide technical design across teams, participate in on-call operations, and improve monitoring, testing, deployment, and incident response for LLM, SLM, multimodal, and agentic model workflows.

Leads end-to-end development of AI scale-up switch platforms, including requirements, vendor selection, hardware architecture, optical interconnects, validation, system integration, and production readiness. Partners with software teams on SONiC, telemetry, diagnostics, and fleet management. Oversees switch integration into AI clusters and leads cross-functional teams across networking, silicon, optics, firmware, software, manufacturing, and operations while optimizing performance, reliability, cost, power, and time-to-market.

Own the vision, roadmap, quality standards, and adoption strategy for catalog APIs powering AI commerce experiences. Lead catalog coverage, product identity, enrichment, ingestion, pricing, availability, freshness, data rights, partner onboarding, metrics, and evaluation initiatives. Partner with engineering, applied science, legal, privacy, security, marketing, and external partners to prioritize investments, guide large senior teams, and scale externally consumed commerce data platforms.

Designs, implements, and owns production-scale inference systems for large transformer and multimodal models. Responsibilities include optimizing CUDA kernels, inference frameworks, batching, caching, quantization, and serving infrastructure; deploying models; monitoring latency SLOs; responding to incidents; and partnering with research teams. The role also drives technical design and establishes inference engineering standards across the AI Infrastructure team.

Create high-volume marketing collateral, proposals, pitch decks, social content, brand assets, and internal materials using traditional design and AI-assisted workflows. Execute typography, layout, refinement, and production in Adobe Creative Suite; maintain brand standards; collaborate with marketing, sales, and leadership; build reusable templates, component libraries, and prompt libraries; prepare production-ready files; and help adopt emerging AI design capabilities.

Leads the strategy, roadmap, and delivery of enterprise business intelligence capabilities. Oversees BI products, semantic models, reporting standards, governance, adoption, and AI-assisted analytics in partnership with Data Engineering, Data Science, IT, and business leaders. Manages and develops the BI team, prioritizes demand, translates business needs into scalable products, monitors performance and value, and remains technically engaged in solution design and troubleshooting.

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.