Top Artificial Intelligence Jobs

Design, build, and deploy large-scale distributed AI/ML applications (IVR, voice, chat) including multi-agent systems and LLMs. Collaborate with product and data science, ensure reliability, scalability, monitoring, and bring research-driven innovations into production using cloud, containers, and IaC practices.

Lead end-to-end design for an AI-native wealth management product: frame ambiguous needs, prototype with real AI, simplify dense financial and legal data into effortless advisor experiences, ship high-fidelity work, and raise design quality across the team as a senior individual contributor.

Develop machine learning methods for 3D particle detection and structural analysis in cryo-electron tomography data, collaborating with interdisciplinary teams on scientific applications.

The Creative Editor/AI leads AI-integrated creative projects, collaborates on content creation, and manages a team ensuring high-quality audiovisual outputs.

The AI Product Owner will lead the lifecycle of AI products, partnering with business stakeholders, translating needs into requirements, and ensuring successful implementation and adoption of AI solutions.

Lead Mission Lane's AI operations strategy end-to-end: identify high-impact AI use cases for contact center operations, build business cases, evaluate vendors, sequence and drive cross-functional execution, establish governance, and measure outcomes in cost, quality, and customer experience.

Design, build, and operationalize reproducible AI/ML pipelines and automation for mission-critical systems. Troubleshoot CI/CD and containerized workloads, integrate AI capabilities with infrastructure and security, and support resilient hybrid compute operations to enhance warfighting decision support.

Design, train, test, deploy, and maintain ML models for cyber national security missions. Collaborate with software engineers and data scientists to productionize AI/LLM solutions, fine-tune open-source models, and build automation (e.g., text summarization). Support containerized deployments and on-prem compute; meet security clearance eligibility requirements.

As an AI/ML Engineer and Data Scientist, you'll analyze data, develop predictive models, and provide insights to clients across various sectors, using advanced statistical techniques and machine learning tools.

Lead design and delivery of enterprise AI solution architectures and roadmaps. Manage a portfolio of AI initiatives, advise executive leadership, and build/deploy advanced systems (LLMs, generative AI, agents, RL, computer vision). Establish secure, compliant MLOps and CI/CD pipelines for regulated environments, transform R&D into governed offerings, mentor teams, and prototype solutions for stakeholder adoption.

The Research Scientist will design methods and experiments for AI control and monitoring, focusing on safety and robustness in advanced AI systems. Key tasks include developing monitoring techniques, researching layered control mechanisms, and collaborating with policymakers and industry experts.

Design, train, test, deploy, and maintain AI/ML models and agentic workflows. Build AI-enabled applications (LLMs, RAG), secure cloud data foundations, event-driven integrations, and MLOps/DevSecOps pipelines. Collaborate with engineers, data scientists, architects, and product owners to deliver mission-critical solutions for the Air Force.

Design, develop, and deploy end-to-end GenAI/LLM solutions on AWS. Build cloud-native, containerized systems (ECS/EKS/Docker/Kubernetes), support production geospatial applications, ensure security/compliance, and deliver production-ready architectures in collaboration with clients and teams.

Design, train, test, deploy, and maintain machine learning models and AI agents for mission-critical defense applications. Define ML strategy, apply best-fit algorithms, implement embedding/semantic search and RAG architectures, and collaborate with data engineers and product owners while ensuring AI safety, evaluation, and responsible practices.

Design, train, test, deploy, and maintain AI/ML models (LLMs, RAG, agentic workflows). Build AI-enabled applications and secure data foundations on cloud (AWS). Implement MLOps/DevSecOps, event-driven integrations, and collaborate with engineers, architects, and product owners to deliver mission-focused Air Force solutions. Secret clearance required.

Lead the design, development, and implementation of AI security products. Collaborate across teams, drive engineering processes, and maintain existing services. Influence product direction and act as a technical expert.

Lead design, build, and deploy scalable Generative AI and ML systems into production. Implement LLM integration, prompt engineering, RAG, conversational interfaces, model monitoring, evaluation frameworks, APIs, inference optimization, and collaborate to productionize forecasting and ML models.

As a Software Engineer focused on generative AI, you will design scalable AI services, optimize APIs, and collaborate with cross-functional teams to enhance enterprise-wide transformation.

The Principal Software Engineer will design, implement, and lead AI security product development, focusing on scalable software solutions across cloud platforms and driving engineering best practices.

Provide technical guidance and implement integrations for Intapp products using Boomi/ETL tools and SQL. Leverage AI and automation to accelerate delivery, manage stakeholder requirements, troubleshoot issues, track project status, and ensure data security, compliance, and measurable outcomes.

As a Senior AI Engineer at Via, you will lead the development of AI products, collaborate with partners, design scalable systems, and shape the technical culture of a new team.

Lead Growth product strategy and execution to drive customer acquisition and onboarding. Partner with GTM, Engineering, Design, and Data to build AI/ML models, automation, and tooling. Set goals, manage product managers, analyze funnel metrics, and operationalize solutions to improve GTM efficiency and business growth.

Lead end-to-end product strategy and execution for the Brex Assistant, an AI agent that automates expense, spend, and travel workflows. Define capabilities, design prompts and evals, prototype, measure, iterate on agent behavior, and partner with engineering, design, and research to deliver a trustworthy, action-taking conversational product used by Brex cardholders.

The Associate Director leads AI and data science projects in Pharma R&D, developing AI solutions, guiding cross-functional teams, and ensuring effective AI product strategies. Responsibilities include implementing AI models, managing data-driven decision making, and overseeing AI ecosystem capabilities, while maintaining a focus on regulatory compliance and user-centric design.

Lead execution and operationalization of enterprise AI initiatives: translate strategy into roadmaps, deliver prioritized programs, drive adoption and value realization, ensure governance and responsible AI, and coordinate cross-functional stakeholders to scale AI solutions.