Top AI Engineer Jobs

As a Generative AI Engineer at Citi, you'll develop and prototype AI solutions, implement machine learning models, manage data pipelines, deploy applications, and collaborate with teams to integrate new technologies.

Design and implement AI solutions, focusing on data pipelines, workflow automation, and ensuring security and governance in a production environment. Collaborate to create reliable, scalable models and optimize enterprise data integration.

The Developer Relations Engineer will enhance on-device AI by enabling developers to run AI models efficiently on Arm platforms. Responsibilities include creating optimization techniques, maintaining implementation references, developing guides, and engaging with the developer community.

As a Forward Deployed Engineer, you will implement AI solutions for enterprises, managing customer deployments and driving ROI through customer-focused technical solutions in robotics.

Lead and define AI architecture, ensuring scalable, reliable AI systems while mentoring engineers and collaborating with product teams.

Lead product strategy and development for AI-native solutions, focusing on user data sovereignty and enterprise integration. Drive market expansion and feature adoption with innovative AI tools and team leadership.

Lead AI/ML engineer responsible for developing and deploying AI solutions in healthcare, collaborating with teams, and designing ML models.

Lead the design and implementation of AI/ML systems, collaborating with cross-functional teams to deliver scalable solutions and mentor engineers.

Drive AI solution deployment for semiconductor technology. Architect AI systems, evaluate model performance, and communicate insights to stakeholders.

The role involves leading security architecture and development for AI Platform, focusing on cryptography, key management, and machine identity. Collaboration across teams is essential to deliver secure solutions.

The Senior Staff Software Engineer will lead the architecture and implementation of AI-powered developer tools and workflows in a cloud environment. Responsibilities include mentoring, driving innovation, managing project delivery, and fostering a culture of continuous improvement.

In this role, you will lead the development of enterprise AI products using Machine Learning technologies. You'll collaborate with cross-functional teams to design and implement features, expanding product reach while ensuring high-quality engineering.

The role involves redesigning software development with AI and automation in a senior engineering position, focusing on improving SDLC efficiency and tool adoption across teams.

Design, develop, and maintain scalable backend systems for automated order-taking platforms, collaborating with teams to integrate AI models and optimize performance across noisy environments.

Develop AI solutions for marketing teams, integrating AI agents and workflows while coaching teams for self-sufficiency in AI use.

The Lead AI Product Engineer will design, build, and operate AI agent systems, focusing on architecture, reliability, and performance while collaborating on user-centric workflows.

As a Staff AI Engineer, you will design and implement AI-powered automation for internal departments, manage the full project lifecycle, and enhance various processes across CargoSprint, focusing on business impact and collaboration.

As a Lead AI Engineer, design and implement AI and machine learning models and pipelines to enhance healthcare outcomes and efficiency.

The role involves architecting a scalable AI platform, building distributed compute solutions, optimizing technologies, and mentoring internal talent in AI and ML.

Assist in developing AI-powered automation and workflows, build production-grade AI solutions, and integrate with enterprise APIs in cloud environments.

Develop AI-powered automation solutions, build REST APIs, orchestrate workflows, and integrate data pipelines in cloud environments.

The Senior AI Engineer will develop AI/ML tools, collaborate on LLM frameworks, optimize data pipelines, and work with security processes.

The AI Engineer will develop and maintain software applications focusing on AI tools, manage data pipelines, and support business operations.

Design, build, and maintain production-grade AI systems and agent-based workflows; own end-to-end pipelines from experimentation to deployment and monitoring; build evaluation pipelines; collaborate with product, data, and GTM; iterate quickly under ambiguity to shape the AI stack.

Lead the technical direction and hands-on implementation of Hilbert's AI stack: design and ship agent-based workflows, production-grade LLM systems, evaluation pipelines, and monitoring. Set architecture and engineering standards, prioritize work, and hire/mentor engineers while collaborating across product, data, and GTM.