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, secure, reusable BI capabilities. Manages and develops the BI team, prioritizes demand, translates business needs into products, monitors business value, and remains hands-on in solution design and technical troubleshooting.

Build and maintain internal applications, AI-assisted workflows, data systems, dashboards, and secure automations for clinical, laboratory, manufacturing, and operational teams. Develop AI features with evaluation, guardrails, human review, and monitoring. Design secure databases, APIs, authentication, audit trails, integrations, testing, deployment, documentation, and regulated-system workflows. Translate business needs into maintainable software, provide production support, evaluate vendors, and mentor junior developers.

Develop AI agents and secure MCP servers for IAM and enterprise applications. Build Python and Node.js backend services, REST APIs, and modern React or Vue.js interfaces. Integrate LLMs and generative AI into existing workflows while applying prompt engineering, tool integration, security, scalability, and performance best practices. Collaborate with engineering and product teams to deliver AI-powered enterprise solutions.

Supports enterprise and site-level adoption of Microsoft Copilot, AI Agents, and other generative AI tools. Partners with employees and business leaders to identify AI use cases, gathers user needs, supports idea-generation sessions, coordinates awareness and training campaigns, and contributes to change management. Also provides technical support to manufacturing operations, analyzes equipment and process data, and identifies improvement opportunities.

Designs, builds, deploys, and operates AI-powered software for mortgage operations and customer experiences. Responsibilities include integrating LLMs and predictive models, developing cloud-native applications on Azure, managing Docker and Kubernetes deployments, creating CI/CD pipelines, implementing infrastructure as code, monitoring production services, optimizing AI workloads, and ensuring security, compliance, fair lending, and responsible AI practices. The role also partners with business teams, guides AI engineering standards, and contributes to long-term technology strategy.

Build and optimize Google Ads and Meta Ads campaigns, with primary ownership of audience targeting, geographic controls, keywords, exclusions, testing, pacing, and tracking. Use AI tools to generate ad variants, automate reporting, and develop workflows for search query review and audience research. Analyze qualified applications, CPA, funded-loan costs, and conversion rates while maintaining accurate measurement and improving lead quality.

The Principal Software Development Engineer leads the architecture and delivery of AI-driven healthcare applications, overseeing full stack development and collaborating with stakeholders to align technical solutions with business needs.

Leads a blended team of software and data engineers while remaining approximately 50% hands-on. Designs data pipelines, platforms, AI/ML applications, GenAI, RAG, and LLM solutions; establishes architecture, engineering standards, MLOps practices, and delivery strategy. Partners with product, data science, and business teams to productionize models, manage roadmaps, solve complex technical problems, develop talent, and deliver measurable business outcomes.

Work with the CEO and department leaders to identify inefficiencies, design AI-powered workflows, automate manual tasks, connect business systems, build internal assistants, train employees, document processes, and measure productivity improvements. The role supports cross-functional strategic initiatives and requires hands-on experimentation with AI and automation tools in a fast-paced startup environment.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, reporting standards, adoption, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable, secure, trusted BI products. Manages and develops the BI team, prioritizes demand, translates business needs into delivery plans, monitors product value, and provides technical guidance on complex initiatives.

Research and develop AI-native numerical algorithms that combine machine learning with scientific and engineering solvers. Build solver-in-the-loop pipelines, learned preconditioners, AI-guided multigrid methods, differentiable solver components, and hybrid ML/numerical methods. Evaluate convergence, stability, accuracy, robustness, failures, resource use, and performance. Collaborate across NVIDIA Research, GPU computing, simulation, engineering, semiconductor, and digital twin teams while shaping the applied research agenda.

Own end-to-end customer data migrations from legacy databases and files into GovPilot. Use AI coding agents to profile data, create mappings, generate transformation and loading scripts, automate validation, and build reusable migration pipelines. Review and correct AI-generated SQL and scripts, identify data quality issues, maintain auditable migration logic, manage multiple client migrations, and support evening or weekend production go-lives.

Develop and deploy AI-powered applications using LLMs, prompt engineering, RAG, agentic workflows, and MCP. Build RESTful APIs, optimize SQL Server databases, integrate 20+ vendor tax applications, and provide L3 support. Lead application analysis, design, testing, implementation, security, and user support while advising stakeholders and mentoring junior analysts. The role also involves feasibility studies, project planning, risk assessment, and enterprise backend development.

Lead AI transformation across Payments Compliance by identifying high-value opportunities, defining use cases and requirements, managing the AI portfolio and roadmap, developing business cases and prototypes, and supporting solution design, testing, implementation, and responsible AI reviews. Partner with compliance subject matter experts, Product, Engineering, Data Science, Legal, Privacy, and governance teams to deliver practical, compliant AI-enabled process improvements.

Leads enterprise adoption of AI, machine learning, generative AI, and intelligent automation across federated engineering teams. Defines reference architectures, standards, reusable patterns, and Responsible AI governance while advising delivery teams on secure, resilient, scalable implementations. Influences senior stakeholders, promotes AI-assisted engineering practices, establishes validation standards, and builds communities of practice to improve consistency, delivery speed, and operational readiness.

Leads development of a next-generation equipment and asset finance platform. Designs, builds, tests, secures, and troubleshoots scalable Java and Spring Boot applications using microservices, REST, Kafka, React, and relational databases. Provides technical direction to a global feature team, mentors engineers, reviews code, drives AI-assisted engineering practices, and contributes to architecture. Improves application stability, observability, code quality, deployment reliability, and operational support across development, staging, and production environments.

Leads semiconductor equipment installation and qualification programs, coordinating equipment teams, manufacturing, facilities, construction, suppliers, procurement, and global stakeholders. The role drives installation quality, safety, schedule adherence, supplier performance, issue resolution, standardization, and continuous improvement. It also applies data, automation, and emerging AI technologies to improve operational processes and factory readiness.

AI Software Engineering Intern contributing to retail applications, AI-powered features, Java back-end services, Vue interfaces, mobile and in-store applications, and CI/CD improvements. The role involves using AI coding assistants, working with LLMs, supporting testing and deployment processes, modernizing legacy systems, and collaborating independently with engineers and stakeholders.

Leads Omnicell’s global privacy program and develops enterprise AI and data governance capabilities. Provides risk-based legal counsel, drafts and negotiates privacy and AI contracts, builds scalable governance processes, advises cross-functional executives, and leads a high-performing team. The role requires translating regulatory requirements into practical business solutions while balancing compliance, customer commitments, product innovation, and commercial objectives.

Owns delivery roadmaps for production AI/ML systems from model concept through deployment and post-launch monitoring. Partners with applied science, data engineering, ML engineering, product, and analytics teams to define milestones, manage dependencies, resolve tradeoffs, track model health and operational metrics, and drive remediation. The role also manages vendor relationships, agile execution, executive communication, and cross-timezone technical programs.

Leads enterprise data platform modernization and AI/ML enablement across hybrid and multi-cloud environments. Responsibilities include architecture assessments, modernization roadmaps, MLOps design, data governance, AI infrastructure readiness, federated data architecture, classified and cross-boundary data management, vendor evaluation, and practice development. The role supports complex federal and defense clients and requires extensive travel and active Secret clearance.

Conduct AI and machine learning research for autonomous trading agents by analyzing large market datasets, applying statistical and machine learning methods, developing models, and identifying trading opportunities. The role emphasizes deep learning, time-series analysis, mathematical rigor, academic research, and coding in C++ or Python within a Linux environment.

Develop scientific AI models for semiconductor engineering by combining physics-based simulation, scientific computing, and machine learning. Build surrogate, operator-learning, and foundation models; create scalable data generation, training, validation, and deployment workflows; collaborate with engineering experts; and publish innovations that advance Scientific AI adoption across engineering applications.

Serve as a pre-sales technical advisor for state and local government agencies adopting Claude. Partner with sales, product, and engineering teams to understand requirements, design scalable AI architectures, support evaluations and deployments, develop performance frameworks, and communicate technical concepts to executives and engineering teams. The role also contributes integration insights to product teams, supports Claude-based development, and requires frequent customer-site travel.

Designs and implements production automation systems, integrations, and AI-agent pipelines across business functions. Evaluates build-versus-buy decisions, establishes standards for testing, monitoring, documentation, and exception handling, improves system reliability, and measures operational value. The role also documents architectures, supports maintainability, and reviews other builders’ work.