Top Artificial Intelligence Jobs

Own and operate a customer pod serving pharmaceutical and medical device clients. Lead AI deployments from pilot to production, manage executive relationships, drive adoption, renewals, and expansion, and hire and develop AI Strategists. Personally oversee high-stakes deployments, advise on AI governance and compliance in regulated environments, translate customer needs into product priorities, and create repeatable deployment playbooks.

Own the full net-new B2B sales cycle, from prospecting and discovery through demos, pilots, negotiations, and closing. Build target account lists, manage pipeline and forecasting in HubSpot, develop relationships across gaming and hospitality markets, attend industry events, and visit Las Vegas properties. Partner with leadership and technical teams to refine messaging, ICP, pricing, qualification, sales stages, and the broader go-to-market playbook. Provide market intelligence and eventually help recruit and develop the sales team.

Develop and maintain BI dashboards and ETL pipelines, transform and integrate structured and unstructured data, build analytical models and forecasts, apply machine learning and distributed computing (Databricks/Spark), create actionable visualizations (Qlik/Tableau/Power BI), and present insights to leadership while working in a cleared defense environment.

Lead the strategy, development, and roadmap execution for AI, automation, and supply chain tools supporting aerospace operations. The role identifies user and business needs, evaluates digital solutions, manages iterative product delivery, improves processes and compliance, facilitates software purchases and deployment, and collaborates with engineering, operations, design, executives, and supply chain partners. Aerospace or safety-critical experience, technical leadership, human-centered design, and up to 10% domestic travel are required.

Owns the AI product roadmap for drilling technology solutions, identifying customer and operational use cases, building prototypes, and translating validated concepts into scalable requirements. Partners with Engineering, Data Science, Operations, Commercial, Cybersecurity, and customers through discovery, pilots, production release, commercialization, and continuous improvement. Evaluates data and model performance, measures business outcomes, and applies responsible AI, security, privacy, and governance requirements throughout the product lifecycle.

Own the applied AI roadmap from concept through production, identifying workflow pain points and translating them into AI-powered tools, automations, and decision-support systems. Build prototypes using LLM APIs, multimodal models, agent frameworks, and orchestration tools, then partner with engineering and vendors to scale successful solutions. Drive stakeholder alignment, adoption, enablement, governance, responsible AI practices, and measurement of business impact across Mattel Digital Studios.

Build AI-assisted, production-ready full-stack applications from concept and prototype through deployment, with a strong frontend focus. Develop accessible React, Vue, and Nuxt interfaces aligned with design systems, implement backend APIs and services, manage SQL and NoSQL databases, and optimize authentication, caching, performance, and scalability. Collaborate with designers and innovation teams while using AI design tools, Figma, specification-driven workflows, and cloud deployment practices.

Lead end-to-end AI product work across Mitratech's shared AI platform and customer experiences. Set strategy and roadmap, convert ambiguous problems into shipped, enterprise-grade features, partner with engineering and design, prioritize based on customer feedback, and represent products to senior stakeholders and customers.

Supports consulting teams by analyzing workflows, identifying AI and automation opportunities, building and testing prototypes, analyzing data, creating reports and user insights, documenting solutions, and presenting recommendations to stakeholders. The internship provides hands-on exposure to AI, automation, technology, and financial advisor business operations.

Own strategic territories and close net-new enterprise software deals. Lead value-based sales cycles from discovery through proof of value, negotiation, and close; build executive relationships; develop account strategies; maintain Salesforce pipeline and forecasts; partner with alliances teams; and advise customers on supply chain resilience, risk, and compliance.

Leads the global sales enablement function, overseeing onboarding, continuous training, certification, account planning, sales kickoffs, and enablement strategy. Develops enterprise sales training curricula, measures program effectiveness, coaches the enablement team, and partners with Product Marketing and Product to align messaging with Tanium’s AI-driven roadmap. Requires experience managing large-scale global enablement programs and up to 10% travel.

Lead end-to-end product design for AI-powered experiences across web and mobile. Partner with product managers, engineers, and designers to simplify complex workflows for frontline users. Translate ambiguous AI opportunities into testable solutions, contribute to scalable design systems, present design rationale, incorporate feedback, and maintain high visual and interaction quality. Use AI tools to accelerate the design process and improve product outcomes.

Architect and operate an enterprise AI workflow platform for Department of the Air Force missions in Azure IL-5 environments. Design secure cloud, container, data, API, RAG, MLOps, monitoring, and disaster recovery architectures; integrate Azure OpenAI, ServiceNow, and DISA networks; and ensure compliance with DoD controls. Lead AI/ML engineering teams, guide use-case development and quality assurance, evaluate LLM solutions, and translate government mission requirements into production-ready AI services.

Build and operate an AI-driven global sourcing platform covering web crawling, data ingestion, normalization, entity resolution, product matching, provenance, and source monitoring. Integrate Zoho CRM and QuickBooks, apply LLMs with structured evaluation and human review, and identify automation opportunities across business departments. Lead pilots, train employees, measure impact, and scale the platform to hundreds of sources.

Leads complex AI, software, and data integration projects in classified intelligence environments. Responsibilities include planning, scheduling, milestone and deliverable tracking, stakeholder coordination, risk mitigation, documentation, status reporting, and application of traditional, Agile, or hybrid methodologies. The role supports intelligence planning conferences, exercises, working groups, capability-development meetings, and mission-partner coordination while aligning technical outcomes with operational objectives.

Build and deploy internal AI tools, LLM applications, and agentic systems from concept through production. Establish reusable engineering patterns, optimize models for cost, latency, and reliability, and create shared infrastructure. Partner with technical teams to deliver practical tools, mentor teammates, and drive autonomous end-to-end execution with strong testing, documentation, evaluation, and operational practices.

Owns the strategy, prioritization, requirements, launch, adoption, and continuous improvement of AI-enabled products. Translates ambiguous healthcare, clinical, operational, and business needs into product roadmaps, PRDs, KPIs, and execution plans. Partners with engineering, data, security, compliance, legal, clinical, and operations teams to deliver responsible, secure, compliant, and measurable AI solutions.

Architects, integrates, fine-tunes, tests, and deploys AI solutions using enterprise platforms, APIs, automation tools, and data services. Builds prototypes, predictive models, and production-ready workflows; evaluates accuracy, bias, groundedness, drift, security, and operational performance. Collaborates with business, platform, architecture, security, data, and vendor teams to define requirements, resolve issues, support adoption, and recommend scalable, maintainable AI capabilities.

Participate in AHEAD’s associate development program, completing technical training, certifications, and project shadowing before contributing to client data and AI solutions. Responsibilities include collaborating across teams, solving technical problems, analyzing issues, making recommendations, managing priorities, and delivering projects. The role requires foundational AI/ML knowledge, Python proficiency, familiarity with generative AI tools, vector stores, cloud platforms, containers, MLOps, and strong communication skills.

Develop production-grade multimodal AI systems for L3/L4 autonomous vehicles. Build sensor-fusion and spatiotemporal world models combining camera, LiDAR, radar, navigation, and vehicle-state data. Create multitask models for road understanding, occupancy, perception, prediction, and planning; develop scalable training and evaluation pipelines; investigate foundation-model approaches; optimize models for real-time NVIDIA hardware; and collaborate across AV engineering teams to deploy robust systems.

Leads the strategy, architecture, and production delivery of agentic AI solutions for Citi’s Client Network Services. The role combines forward-deployed client engagement, hands-on full-stack engineering, cloud-native platform development, security, infrastructure, and engineering leadership. Responsibilities include building with Google ADK and MCP, developing Python and Java services with React interfaces, operating Kubernetes platforms, managing migrations, improving SDLC practices, mentoring engineers, and aligning technical roadmaps with business priorities.

Build and operate governed production data pipelines in Databricks using medallion architecture, Unity Catalog, data quality controls, lineage, and semantic models. Develop AI agents and retrieval-augmented applications grounded in enterprise data using Mosaic AI and model serving. Integrate enterprise systems through APIs and events, implement security and observability, and own architecture, testing, CI/CD, deployment, and production support.

Build and deploy practical AI solutions, including internal AI agents, intelligent search, workflow automation, document intelligence, custom applications, and SaaS integrations. Establish AI infrastructure, security, governance, evaluation methods, and best practices. Partner with business teams to prototype solutions, identify automation opportunities, evaluate build-versus-buy decisions, and train employees on AI tools.

Supports the GTM Lead and founders across sales, growth, and content. Responsibilities include creating technical content for AI products, running growth experiments, supporting outbound initiatives, building the sales funnel, communicating with technical buyers, and collaborating with engineering in an early-stage environment.

Build Lingopal’s go-to-market motion for its evolving AI agent platform. Develop positioning, target accounts, outbound strategy, sales processes, and pricing inputs. Own enterprise sales from prospecting through discovery, pilots, and closing across customer-support-heavy enterprises and scaling AI-agent companies. Engage senior buyers including Chief AI Officers, COOs, and CTOs, while feeding market insights back into product strategy.