Top Artificial Intelligence Jobs

Manages global Sales Development Operations across North America and the UK. Builds an SDR Operations Center of Excellence, owns workflows, reporting, Salesforce governance, technology roadmaps, AI and automation initiatives, vendor relationships, documentation, training, and adoption. Leads two direct reports while supporting routing, data quality, system access, process improvement, operational governance, and cross-functional delivery across Sales, Marketing, IT, Data, and Sales Operations.

Leads and scales a customer-embedded Forward Deployed Solutions Engineering organization focused on AI, cloud architectures, enterprise data platforms, and mission-critical systems. Builds and mentors technical teams, partners with C-level customers and Cisco/Splunk leadership, translates deployment insights into product innovation, and delivers prototypes and technical solutions that accelerate adoption, retention, and expansion.

Supports the Solutions Architecture team by helping design customer technology solutions across networking, security, AI, analytics, and data center environments. Responsibilities include documenting requirements, creating bills of materials, maintaining demonstrations, researching technical solutions, communicating with sales teams, and troubleshooting configuration conflicts. The internship includes customer exposure, mentoring, technical training, and in-person work at the Denver office.

Supports operational due diligence reviews of traditional and alternative investment managers. Analyzes manager documentation, identifies operational risks and inconsistencies, contributes to written reports and recommendations, and helps improve team processes through technology, automation, data analysis, and generative AI. The role requires collaboration, strong analytical and communication skills, attention to detail, and domestic travel of less than 10%.

Lead, coach, and mentor senior account executives selling Workday cloud, SaaS, and ERP solutions to federal systems integrators, Department of War, and Intelligence Community customers. Drive new business, manage complex sales cycles, coordinate presales and internal teams, cultivate partner relationships, position Workday against legacy ERP systems, and maintain accurate forecasts and business models while delivering revenue and quota attainment.

Develop predictive models, algorithms, data pipelines, analyses, dashboards, and visualizations using large structured and unstructured datasets. Collaborate with clients and teammates to translate complex data into actionable insights and support informed decisions. The role requires expertise in Python, PySpark, R, SQL, Palantir Foundry, Power BI, statistical programming, and data science techniques, along with a Secret clearance.

Lead client-facing data science work: design and develop ML/AI solutions, build and monitor operational data pipelines, query/migrate data via APIs, use SQL/NoSQL and cloud architectures, guide teammates, and translate complex data into actionable insights. Requires TS/SCI with polygraph and extensive data science experience.

Lead data science projects to extract insights from structured and unstructured data using AI/ML and IoT. Work with clients, guide teams, develop algorithms and systems, process geospatial and varied file formats, build visualizations, and deliver data-driven recommendations.

Develop deep learning and AI/ML models to predict cardiac events from ECG and physiological signals. Apply signal processing, analyze implantable-device datasets, build Python tools, validate algorithms, and support feasibility studies for diagnostic features. Collaborate with clinical, software, and hardware teams to improve implantable-device performance and patient outcomes.

Provides technical leadership for data science, engineering, and software teams developing machine learning applications for manufacturing and process industries. Develops AI, modeling, simulation, and cognitive computing solutions; evaluates emerging technologies; collaborates with customers and product teams; and represents the company at industry and academic events. Requires strong expertise in mathematics, statistics, optimization, machine learning, and software development, with a focus on delivering research-driven customer value.

Leads the organization’s technology function, managed services relationship, vendor governance, technology strategy, cloud data modernization, automation and AI enablement. Oversees infrastructure, security, compliance, data governance, business continuity, and technology investments while advising executives and the Board. Manages the Strategic Data Analyst and develops the long-term internal technical capability and talent strategy.

Leads the global Accelerate developer program as a business capability, owning strategy, design, delivery, operations, financial performance, scalability, and partner outcomes. Builds operating models, governance, tools, metrics, and developer pathways from discovery through commercialization. Partners with product, technology, marketing, growth, delivery, finance, regional teams, and healthcare ecosystem leaders while managing executive relationships, program economics, quality, risks, and continuous improvement.

Leads enterprise change management for data, analytics, and AI initiatives. Develops adoption strategies, impact assessments, communications, training, sponsorship, coaching, and resistance-management plans. Partners with technical teams, executives, and business stakeholders to implement data platforms, governance frameworks, AI applications, automation, and process changes. Measures adoption and business value while building organizational change capability and supporting leadership through large-scale digital transformation.

Leads data and analytics strategy, delivery teams, and multidisciplinary data engineering functions across architecture, analytics, and governance. Develops people, drives business use cases, improves data ecosystem reliability, and partners with technology owners and business stakeholders. Requires strong modern data architecture knowledge, experience leading data and AI teams, and executive communication skills. Preferred experience includes machine learning, scalable cloud-native solutions, infrastructure as code, Agile practices, cybersecurity, and aerospace compliance.

Leads advanced analytics engagements across pharmaceutical launches, therapeutic areas, and enterprise initiatives. Defines business questions, selects methodologies, oversees analytical execution, translates complex datasets into insights, and delivers executive recommendations. Focus areas include promotion effectiveness, resource optimization, causal inference, driver analysis, segmentation, predictive modeling, and precision health. Partners with senior stakeholders and globally distributed analytics teams while quality-assuring work and contributing to reusable analytical capabilities.

Develops AI agents, automation tools, predictive models, and decision-support solutions using structured and unstructured data. Leads AI projects from conception through deployment, evaluates analytical approaches, and collaborates with engineers, architects, product managers, and business stakeholders. Applies statistical and mathematical techniques, develops performance metrics and reports, communicates technical findings, and uses Python, SQL, and cloud technologies to solve complex business problems.

Leads enterprise sales enablement strategy across proposal development, account management, reporting, analytics, clinical support, content, technology, producer strategy, compensation, and governance. Partners with sales and account management leaders to improve growth, retention, customer experience, and sales effectiveness. Oversees AI and Salesforce-enabled transformation, operating plans, budgets, multidisciplinary teams, and cross-functional execution in a complex healthcare organization.

Leads enterprise supervision talent and development strategy across Home Office and Field teams. Oversees onboarding, training, licensing readiness, quality review, leadership development, and continuous improvement. Builds scalable learning programs, aligns capabilities with regulatory and business needs, uses data and artificial intelligence to improve feedback and quality, and leads a multidisciplinary team while influencing senior stakeholders across the organization.

Lead revenue generation for Squark AI by building enterprise pipeline, selling AI software and related agency services, closing complex B2B deals, and shaping repeatable go-to-market strategy. The role owns prospecting through close, executive relationship development, ROI-based business cases, pricing, negotiations, forecasting, CRM discipline, and cross-functional collaboration with product, marketing, analytics, and delivery teams.

Manage demand planning and forecasting for North America supply chain operations. Analyze sales trends, demand drivers, forecast accuracy, and large datasets; develop consensus forecasts across multiple time horizons; coordinate with sales, marketing, finance, supply planning, customers, and global teams; support inventory strategies, S&OP, risk mitigation, process automation, and AI-enabled forecasting improvements.

Drive consultative B2B sales growth across the broadband industry by developing new clients, expanding existing accounts, selling consulting, engineering, and managed services, and building long-term executive relationships. The role requires strategic account and opportunity planning, disciplined CRM usage, collaboration with subject-matter experts, AI curiosity, pipeline forecasting, and representation at client and industry events. Regular travel to clients and conferences is expected.

Lead learning and development for the Cisco account by diagnosing capability gaps, consulting with senior stakeholders, designing and facilitating leadership, skills, onboarding, and AI upskilling programs. Manage L&D strategy, performance and succession planning support, program evaluation, KPIs, and budget allocation. The role includes direct facilitation, hands-on execution, and management of one L&D Project Manager.

Conduct independent AI research spanning large language models, reasoning, knowledge acquisition, factuality evaluation, and trustworthy AI. Translate research ideas into scalable prototypes, implement and extend state-of-the-art methods, design experiments, develop algorithms and evaluation methods, use AI-assisted development tools, and communicate findings through technical reports and research papers.

Lead research into novel AI architectures, learning algorithms, reasoning, knowledge representation, and evaluation methodologies. Define and execute ambitious research programs, design experiments, develop large-scale content evaluation systems, mentor research engineers, and communicate findings through technical publications. The role combines scientific leadership with hands-on innovation focused on language models, factuality, evidence quality, source reliability, and trustworthy AI systems.

Leads a team of forward-deployed AI engineers delivering production solutions for business functions. Owns AI use-case prioritization, technical quality, governance reviews, champion-network enablement, stakeholder partnerships, and team development. Directs solutions from design through deployment, ensures testing and security standards, coordinates Legal, Privacy, Information Security, and Procurement reviews, and promotes AI adoption through training and ongoing support.