Top Artificial Intelligence Jobs

The Senior Principal, ML/AI will lead cross-functional teams in developing and implementing ML/AI solutions, driving significant business impact through innovative technical leadership over a defined roadmap.

Lead cross-functional ML/AI initiatives, drive technical roadmaps, mentor teams, and deliver impactful ML/AI solutions for business growth.

The role involves teaching, strategic leadership, and administrative oversight for the MS in Health Informatics Program, ensuring curriculum relevance and program success across multiple campuses.

The Principal Research Scientist will lead research on resilient AI, manage projects, publish findings, secure grants, and supervise staff and students.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

The Engineer II will perform complex engineering tasks, lead projects in thermoforming engineering, manage project costs, and support continuous improvement initiatives while promoting safety and collaboration within the team.

Leads enterprise architecture, technical strategy, and evolution of GEICO’s Generative AI, virtual agent, and agentic workflow platforms. Designs scalable systems for retrieval, knowledge management, prompt and context management, orchestration, semantic search, and action execution. Evaluates technologies, establishes GenAI application standards, guides production deployments, influences business strategy, mentors senior engineers, and serves as a final technical authority across multiple teams and business domains.

Supports AI and machine learning modernization projects by identifying integration opportunities, developing and testing AI-assisted tools, researching frameworks and APIs, collaborating with scientists and IT teams, and documenting workflows and outcomes. The intern will help automate internal business and laboratory processes and must work onsite in the Pittsburgh metro area during Fall 2026.

Leads enterprise SEO and AI discovery strategy across search engines, answer engines, and AI platforms. Owns roadmaps, technical discoverability, content architecture, entity optimization, structured data, KPI reporting, experimentation, and competitive analysis. Partners with marketing, product, UX, engineering, and content teams to improve visibility, citations, recommendations, traffic, engagement, and conversions. Influences backlogs, communicates executive recommendations, and coaches SEO and content contributors.

Leads development of scalable cloud-native payments and POS software, translating requirements into reliable technical solutions. Drives architecture, software quality, automated testing, CI/CD, observability, production issue resolution, and continuous improvement. Provides technical leadership, mentors engineers, collaborates with product and customer-facing teams, and incorporates customer feedback into product enhancements. The role also promotes modern engineering practices, including AI-assisted development.

Manage and govern the Microsoft 365 AI and automation platform (Power Platform, Copilot Studio, Azure AI). Own architecture, environment strategy, DLP and connector governance, integration with Azure and enterprise systems, monitoring, cost control, security compliance, and a Power Platform & AI Center of Excellence while partnering across infrastructure, security, and business teams.

Build and operate an enterprise AI governance program: author the AI-SSDLC, gate agent deployments, lead threat modeling/red teams, monitor AI behavior and compliance, align with Legal/Privacy/Compliance, and implement automation and dashboards for executive reporting.

Assist cloud and generative AI teams in designing, building, testing, and deploying AI agents, agentic workflows, AI-powered web applications, RAG pipelines, and enterprise LLM integrations. The intern will support prompt engineering, evaluate AI outputs, write documented Python code, participate in reviews, gather requirements, and collaborate with cross-functional teams in a hybrid environment.

Build the core agentic platform for global trade, including tool routing, policy enforcement, memory, context graphs, evaluation infrastructure, APIs, and scalable production systems. The role focuses on making AI agents reliable enough to execute financial and operational actions using messy enterprise data. Responsibilities include product ownership, customer collaboration, system design, production delivery, and potentially recruiting and mentoring engineers.

Owns enterprise AI product strategy, roadmaps, backlogs, requirements, governance, and prioritization across multiple platforms. Leads stakeholder alignment, Agile ceremonies, UAT standards, release sign-off, testing strategy, automation adoption, and root-cause analysis. Partners with UX, architecture, QA, and release teams to ensure delivery readiness, monitors product performance, gathers feedback, and advises senior leadership on product decisions and measurable business outcomes.

Build and operate custom AI agents for private-market clients end to end, from discovery and requirements through deployment, rollout, adoption, and ongoing iteration. Design agentic systems with retrieval, context design, tool and MCP integrations, orchestration, evaluation, observability, and cost controls. Work directly with clients, make product and engineering trade-offs, manage cloud infrastructure, document solutions, train users, and mentor less experienced engineers.

Design, develop, and maintain enterprise AI applications, including conversational assistants, copilots, autonomous agents, RAG solutions, and workflow automation. Build scalable APIs and microservices integrating foundation models and enterprise systems. Apply prompt and context engineering, memory management, observability, governance, and performance optimization. Collaborate with cross-functional teams to identify automation opportunities and participate in Agile development, code reviews, CI/CD, and DevSecOps.

Build and improve Swayable’s AI and analytics engine using Python, scientific computing, machine learning, and distributed systems. Develop scalable, high-performance software, optimize parallel computing architecture, productize AI and data analysis capabilities, and collaborate with engineers, data scientists, and researchers. The role also includes designing new features, maintaining testable code, mentoring junior engineers, documenting decisions, and providing technical feedback.

Build and optimize Swayable’s AI and analytics engine using Python, scientific computing, machine learning, and distributed systems. Responsibilities include architecting scalable high-performance computing solutions, productizing AI and data analysis, developing new features, maintaining code quality, collaborating with engineers and researchers, and mentoring junior engineers.

Build and deploy production-grade AI applications using Python and Azure. Develop LLM, RAG, and agentic workflows; integrate enterprise platforms, APIs, databases, and Microsoft 365; and create scalable backend services. Partner with stakeholders to translate ambiguous business needs into production solutions while applying strong testing, security, observability, scalability, and performance practices.

Design, develop, and apply AI and machine learning models for mission-critical defense applications. Build multimodal sensor, computer vision, NLP, and large language model solutions using Python and ML frameworks. Analyze large datasets, implement computational models and algorithms, collaborate with software engineers in agile teams, transition research into production-ready software, support proposals and technical reports, and present work to customers and professional audiences.

Own budgeting, forecasting, financial modeling, monthly reporting, SaaS metrics, scenario analysis, and board reporting. Build and maintain AI-driven finance workflows using Claude, automate recurring analysis, validate outputs, and document data lineage. Partner with accounting, Data and Analytics, Sales, Marketing, Product, and G&A to explain results, manage budgets, evaluate investments, and deliver reliable reporting. Support month-end close and maintain trusted BI data sources.

Lead regional enterprise sales for NVIDIA’s Physical AI and digital twin solutions. Build executive customer and partner relationships, develop end-to-end solution sales plays, enable global sales teams, manage lighthouse opportunities, track market adoption, and provide customer insights to product teams. The role focuses on industrial manufacturing, factory planning, robotics, synthetic data, intelligent infrastructure, and expansion across APAC and the Americas.

Build and maintain production AI/ML applications, backend services, data pipelines, and machine learning models. Develop agentic AI systems, LLM and RAG solutions, and MLOps capabilities including monitoring, versioning, A/B testing, and retraining. Collaborate with product, software, platform, and data teams to deliver reliable, explainable, and performant AI solutions for financial markets.

Lead assessment and modernization of NASIC data management: inventory assets, design scalable secure architectures, implement lifecycle governance, ensure data quality and integration, and apply ML/AI and visualization to derive actionable intelligence. Provide recommendations, training, and capacity building for IC personnel.