Top Artificial Intelligence Jobs

As a Staff Software Engineer, you'll develop AI-native product features, integrate with EHRs, and ensure compliance, focusing on quality and safety in healthcare applications.

The AI Data Specialist supports AI tool sets, manages data solutions, collaborates with teams on data structures, and interacts with clients to address data needs and improve operational outcomes.

As a Technical Product Manager for AI Enablement, you will lead product vision and execution for AI platforms, working with cross-functional teams to ensure successful adoption of AI solutions throughout the company.

Design and implement AI-powered solutions for document extraction and financial reasoning, focusing on ML pipelines and application of LLMs.

Join Uplane as a founding AI engineer to develop scalable AI systems. Responsibilities include building AI models, managing databases, and ensuring product alignment with user needs.

The AI Marketing Strategist will manage client relationships, advise on digital marketing, execute projects, and implement technology solutions to enhance marketing value.

The Director of AI & Data Analytics will lead the AI strategy, mentor teams, build scalable data solutions, and ensure data governance, focusing on transforming data into actionable insights.

The Senior AI Quality Engineer ensures AI applications are reliable and safe in mission-critical environments, building custom testing frameworks and evaluating AI system performance through all development phases.

The Forward Deploy Engineer collaborates with sales to design and implement proofs of concept (POC) for enterprise clients, focusing on integration and workflow optimization while providing product feedback to improve offerings.

As a Software Engineer II, you will design, develop, and maintain AI-driven mobile features, collaborating across teams to enhance mobile experiences used by millions.

The Software Engineer II will design and maintain fullstack systems for AI-powered features, develop scalable services, and collaborate with product teams, focusing on innovative consumer experiences.

Build and improve AI/ML systems and data pipelines for a B2B SaaS platform; shape product and technical strategy; work with customers; mentor team members; ensure secure, robust, and scalable infrastructure.

Lead and deliver enterprise AI-ready data platform transformations: design cloud-native architectures, prototype AI-assisted pipelines, embed governance and compliance, mentor teams, and partner with executives to modernize data systems for real-time analytics and AI use cases.

Lead end-to-end onboarding for enterprise customers: run discovery, design solutions, configure systems, build integrations, manage escalations, adopt AI-driven workflows, and drive go-lives ensuring fast customer value.

The Integration Engineer will build enterprise integrations for AI platforms with Microsoft Graph, focusing on API integration, security, and performance optimization.

The Integration Engineer develops enterprise integrations for AI systems using Microsoft Graph API, ensuring secure authentication and data flows while collaborating with senior engineers for production code implementation.

Lead the Customer Success Team to drive adoption and enablement of Labs capabilities among consultants, ensuring measurable business impact and user engagement.

The role involves building and maintaining data infrastructure, conducting advanced analytics, and developing AI-enabled systems to drive insights for grantmaking for social change.

The Head of Customer Success leads a team to enhance consultant adoption of AI tools, drive performance metrics, and advocate for user feedback, while also managing operations and support.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.

The Full Stack AI Engineer will design and maintain AI applications, develop backend services, collaborate with data scientists, conduct code reviews, and advise on AI technologies. The role requires extensive Python experience and the ability to obtain a DHS Public Trust clearance.

Lead the end-to-end product development process, conduct market research, collaborate with cross-functional teams, and manage product roadmaps based on customer insights and analytics.

As Lead Edge AI Engineer, you'll architect edge-AI pipelines, build developer-friendly APIs, optimize performance, and mentor engineers while collaborating on decentralized AI solutions.

The Research Engineer will advance AI and biology research by implementing models, driving projects, and collaborating with teams to solve biological problems.

The Generative AI Specialist will develop and implement AI models, collaborate with teams, ensure ethical standards, and mentor engineers.