Top Artificial Intelligence Jobs

Develop and integrate cloud software supporting cyber intelligence and AI/ML capabilities on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java development, RESTful services, distributed systems, cloud deployment, DevOps, container orchestration, testing, integration, Linux scripting, and troubleshooting. The role also involves big-data technologies, Hadoop ecosystems, LLMs, RAG, analytics, and secure software engineering for national security missions.

Design, develop, test, deploy, and operationalize AI/ML algorithms for mission and business requirements. Build scalable production models, integrate data pipelines, evaluate model performance, and manage training, retraining, monitoring, and continuous improvement. Apply statistical analysis, data governance, software architecture, and data modeling principles. Support system integration and verification/validation activities, with potential leadership of distributed teams and technical customer engagement.

Provides system administration for UNIX, Linux, Solaris, and Windows environments supporting cyber intelligence and AI/ML capabilities. Maintains client/server, storage, network, and mobile systems; performs monitoring, troubleshooting, capacity planning, performance tuning, configuration, and Tier 1 and Tier 2 support. Requires active TS/SCI clearance with polygraph, five years of system administration experience, technical education or equivalent experience, Security+ certification, scripting skills, networking knowledge, and Oracle administration experience.

Provides Tier 1 and Tier 2 IT support, system monitoring, troubleshooting, configuration, maintenance, and user assistance for UNIX, Windows, network, storage, and client/server environments. Manages daily system operations, resolves hardware and software issues, maintains system integrity, and supports cyber and AI/ML capabilities hosted on compute clusters and AWS infrastructure. An active TS/SCI clearance with polygraph and Security+ certification are required.

Designs, develops, tests, deploys, and improves machine learning models for business and mission requirements. Responsibilities include selecting datasets, performing statistical analysis, integrating data pipelines, training and retraining models, monitoring performance, applying evaluation protocols, and overseeing system integration. The role requires knowledge of model architecture, infrastructure, data engineering, governance, and scalable AI/ML solutions, with potential leadership of distributed teams and customer engagement.

Develops system requirements, architectures, designs, technical documentation, and integration and test plans for cyber and AI/ML capabilities. Leads systems engineering activities across requirements allocation, interfaces, configuration control, verification, and system implementation. Supports large-scale compute clusters and AWS Cloud infrastructure while coordinating with government stakeholders and cross-functional teams. Requires active TS/SCI clearance with polygraph and seven years of comparable systems engineering experience.

Administer, monitor, troubleshoot, and maintain large Hadoop clusters and AWS cloud infrastructure supporting AI/ML and national security missions. Manage Linux systems, scripting, provisioning, configuration management, distributed storage, hardware diagnostics, security practices, and cloud services. Collaborate across mission-focused teams, lead complex technical tasks, train junior staff, and support technologies including Kubernetes, Docker, load balancers, and observability platforms.

Build, integrate, test, deploy, and maintain AI-enabled applications, APIs, model services, automation workflows, and user-facing tools. Translate data science prototypes into production-ready software, implement evaluation and monitoring, optimize models and prompts, and collaborate with engineers and domain experts. The role requires Python, software development fundamentals, machine learning knowledge, Git, testing, and project experience, with preferred exposure to modern AI frameworks, cloud, containers, retrieval-augmented generation, and model evaluation.

Own strategic healthcare customer relationships, quota attainment, account expansion, renewals, and retention. Diagnose clinical and operational workflow challenges, build executive-level business cases, guide customers toward appropriate AI solutions, and partner with Clinical Engineers on technical implementations. Monitor product usage, identify upsell opportunities, forecast expansion pipeline, and drive adoption of Heidi’s AI-powered healthcare workflows.

Designs, builds, and operationalizes enterprise AI, generative AI, machine learning, and agentic AI solutions. Develops integrations, orchestration services, reusable tooling, deployment pipelines, monitoring, and governance controls. Partners with architecture, platform, data, and product teams to deliver scalable, secure, compliant AI capabilities across the organization.

Entry-level AI operations role supporting an Austin-based sports academy. Responsibilities include running ads, creating AI videos, building websites, automations, dashboards, and internal tools, screening candidates, managing tasks, and experimenting with AI workflows. The role emphasizes autonomy, rapid learning, organization, adaptability, and producing real work using AI-first tools.

Provides senior legal counsel on AI, product development, marketing, legal technology, technology transactions, and emerging regulations. Advises Product, Engineering, Marketing, Partner, Customer Success, and Strategy teams; drafts policies and agreement terms; negotiates vendor, open-source, collaboration, and customer agreements; supports product launches and go-to-market strategies; and translates complex AI laws into practical business guidance.

Leads billing and accounts receivable operations, including invoicing, collections, reconciliations, cash application, dispute resolution, forecasting, and month-end support. Manages billing and AR staff while developing AI-enabled tools, dashboards, automation workflows, and predictive analytics. Partners with Finance, Accounting, IT, Operations, and customer-facing teams to improve data quality, controls, reporting, and process efficiency.

The AI Solutions Analyst identifies business opportunities for generative AI and process automation, translates requirements into scalable solutions, develops prompts and workflows, monitors AI quality, supports testing and adoption, creates documentation and training, and measures business impact. The role partners across business and IT teams and serves as an enterprise AI productivity tools subject matter expert.

Leads enterprise AI enablement and hands-on scientific data science in a biotech environment. Partners with cross-functional teams to identify and deploy AI and automation solutions, build reproducible pipelines, and support AI governance and adoption. Conducts human genetics, bioinformatics, real-world evidence, biomarker, clinical, and translational analyses using diverse biomedical datasets. Develops visualizations, dashboards, documentation, and training materials to inform research and program decisions.

Assists with human-AI interaction research projects by designing experiments, following protocols, collecting and analyzing data, maintaining detailed records, summarizing statistics, writing technical reports, and developing solutions to research obstacles. May build quantitative models and program software in support of research activities. Collaborates with project teams and contributes to experiment documentation and results presentation.

Leads evaluation, deployment, integration, and operation of secure generative and agentic AI tools, LLMs, and self-hosted multi-GPU infrastructure. Develops AI services, APIs, MCP servers, sandboxed environments, engineering-system integrations, and AI-assisted workflows. Measures reliability and effectiveness, documents recommended practices, supports technical teams, and evaluates emerging technologies across software, robotics, embedded, FPGA, and other engineering domains.

Conduct AI security research focused on AI assurance, red teaming AI systems, and digital forensics, response, and mitigation. Develop and test security tools, analyze findings, document results, and collaborate with engineers and researchers. The internship requires knowledge of AI/ML, cybersecurity, programming, networking, and common machine learning frameworks. This is a part-time, onsite role in Pittsburgh during Fall 2026 and Spring 2027.

Conduct AI security research and development focused on AI assurance, red teaming AI systems, and AI digital forensics, response, and mitigation. Document research findings and collaborate with engineers, researchers, and cross-functional teams. The internship requires knowledge of AI/ML, cybersecurity, programming, networking, and related tools, with work performed part-time onsite at the SEI Pittsburgh office during Fall 2026 and Spring 2027.

Owns end-to-end delivery of complex AI and software functionality from research through production. The role coordinates perception, machine learning, behavior, software, and hardware teams; manages plans, milestones, risks, dependencies, and trade-offs; and establishes program-delivery frameworks. It partners with engineering leadership and product stakeholders to align execution with the roadmap while translating uncertain research into predictable, shippable outcomes.

Leads product marketing for RealPage’s Agentic AI solutions, driving go-to-market strategy, positioning, product launches, customer adoption, competitive intelligence, sales enablement, and marketing content. Partners cross-functionally with product, sales, account management, and demand generation teams while representing the customer voice. Develops messaging, buyer journeys, launch KPIs, and strategic recommendations for AI, data, and analytics products serving the multifamily real estate industry.

Architects enterprise AI/ML systems, including training pipelines, inference services, feature stores, data ingestion, and MLOps frameworks. Leads multidisciplinary engineering teams, defines technical roadmaps, oversees execution, and interfaces with senior government stakeholders. Establishes secure engineering, DevSecOps, testing, and model governance practices while guiding cloud-native integrations, advanced ML tool adoption, responsible AI, architecture reviews, and strategic planning for Defense Intelligence Agency missions.

Build the enterprise platform for an AI creative product, including workspaces, roles and permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services and APIs for multi-tenant usage patterns alongside polished React/Next.js administration and billing experiences. Collaborate with founders, sales, and customers to convert requirements into production features while taking increasing ownership of enterprise platform surfaces.

Architects, develops, and maintains cloud-native C#/.NET applications and AI-powered solutions on Azure. Designs and deploys AI agents, RAG systems, prompt workflows, tool calling, and vector search capabilities. Establishes engineering standards, makes architectural decisions, conducts code reviews, mentors developers, and translates business needs into technical roadmaps. Integrates responsible AI practices, security, privacy, evaluation, and governance throughout the software development lifecycle.

Lead architecture and implementation of Klaviyo's Customer Agent platform: design scalable agentic/LLM systems, drive technical strategy, ship AI-powered features, ensure reliability and observability, mentor engineers, and partner cross-functionally to deliver conversational AI at scale.