Top Remote AI Engineer Jobs

The Forward Deployed Engineer will embed within customer teams to solve complex business problems, drive AI adoption, and provide feedback to the Product team.

The role involves improving AI cluster resiliency, developing AIOps solutions, automating workflows, and delivering presentations while collaborating with customers and teams.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

Develop and optimize AI-driven solutions for healthcare automation, integrating features, and collaborating with engineers to address business needs.

Lead the development of AI products, design scalable systems, advance AI foundations, collaborate with stakeholders, ensure quality practices, and mentor engineers.

The AI Software Developer will design, craft, and optimize AI prompts, moving prototypes to operational systems, and architect scalable infrastructures for agentic AI systems.

The Senior AI Software Engineer will design scalable AI infrastructure, develop AI-driven features, and collaborate on product development, ensuring system reliability and performance.

The role involves synthesizing, placing, and routing high-speed designs, collaborating with RTL teams, and optimizing designs for power/performance area.

Design, build, and operationalize AI agentic solutions across the software lifecycle. Own backend responsibilities, contribute to frontend, define technical requirements, deliver maintainable code, collaborate with clients, and stay current with AI, LLM orchestration, and evaluation practices.

As a QA Automation Engineer, you will develop automated and manual testing frameworks, validate AI systems, and collaborate with teams to ensure quality and coverage.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

The Senior Math Libraries Engineer will design, develop, and optimize HPC software for AI and matrix operations, while leading projects and mentoring. Collaboration with various teams and technical leadership are key responsibilities.

The Software Engineer - AI Systems will design and implement systems to coordinate LLMs, build testable software stacks, conduct research, and collaborate with team members to create AI-powered security solutions.

The Sr. Staff Software Engineer will design and implement scalable systems for Conversational AI and automation, collaborating with teams to deliver solutions, mentor engineers, and ensure system reliability.

The job involves designing and building features for various user segments utilizing AI in workflows, mentoring team members, and contributing to engineering practices.

The role involves implementing AI features like computer vision and NLP, improving search quality, building Python APIs, and collaborating on solutions.

The Senior Software Engineer will innovate in AI, lead software development lifecycle, design microservices, mentor peers, and ensure engineering excellence.

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.

As a Full Stack Engineer, you will build AI-powered applications, manage client interactions, and apply best practices in MLOps and LLMOps.

As a Senior Software Engineer in Agentic AI, you will develop AI-driven software translation tools, design workflows, and collaborate with specialists to enhance code generation pipelines.

As a Consulting Systems Engineer, you will lead technical pre-sales, design AI and data solutions, and engage with customers to define integrated technology solutions.

The Staff Software Engineer, AI/ML Focus will lead AI product development, ensure system reliability and security, and collaborate with cross-functional teams to innovate tools and products.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The role involves developing scalable backend systems in Go and other languages, building high-volume analytics, and designing APIs for ML workflows.