Top Remote AI Engineer Jobs

The AI Engineer will develop an Enterprise GenAI platform, design RAG systems, build AI pipelines, and implement evaluation frameworks while collaborating with cross-functional teams.

Build and maintain AI tools for internally at Automattic, focusing on enhancing productivity through LibreChat while collaborating with the team.

The Applied AI Engineer will develop and ship AI features across Automattic's products, collaborating with teams and scaling innovations that impact millions of users.

Design and build a unified evaluation platform and automated pipelines to evaluate LLM-based agents at enterprise scale. Implement observability, tracing, feedback loops, and guardrails; integrate LLMs, retrieval, embeddings, and orchestration; partner with product and ML teams to turn production failures into evaluation cases.

Lead the development of AI/ML systems for document processing, mentor engineering teams, and implement advanced machine learning solutions focused on language models and data extraction.

Design and build autonomous, enterprise-grounded AI agents and workflows using the Elastic Stack, RAG, and LLMs. Integrate models with internal APIs and SaaS, manage deployment and scaling on cloud/Kubernetes, ensure security/compliance, document systems, and provide technical leadership for agent lifecycle and performance optimization.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

As a Staff Software Engineer on the AI DevX team, you will develop tools and infrastructure for AI-driven engineering, promote best practices, and enhance developer productivity.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

As a Junior Backend Developer, you'll translate UI/UX designs into code, integrate with APIs, and utilize AI tools for efficiency.

The Software Development Engineer in Test will design and maintain an automated testing framework for AI systems, ensuring reliability and performance through extensive testing, debugging, and collaboration with system engineers.

The AI Principal Engineer will drive the AI product vision, collaborate closely with the CEO, design key features, and lead a team of AI engineers in a fast-paced startup environment.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

As a Senior AI/ML Engineer, you will design and deploy LLM systems, collaborate with cross-functional teams, and manage model deployment in production environments.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

The AI/ML Software Engineer will design, implement, and maintain AI features and ML models for Rocket Lawyer's platform, working closely with cross-functional teams.

Design, prototype, and deploy production-ready AI products using ML and generative AI. Lead cross-functional teams, collaborate with stakeholders to solve workflow problems, build scalable prototypes and proofs-of-concept, and apply latest ML/GenAI research techniques.

The Senior AI Software Engineer will design and develop backend systems integrating Generative AI technologies, ensuring performance, scalability, and security within enterprise applications.

This role involves developing AI-driven features, building a semantic data layer, collaborating across teams, and resolving production issues.

Develop full-stack systems for AI financial agents, create scalable APIs, and collaborate with AI researchers on data integration and performance optimization.

Lead the buildout and scaling of AI capabilities at Optimal Dynamics, establishing engineering standards and delivering production systems. Own end-to-end initiatives from data readiness to production launch, collaborating cross-functionally and mentoring teammates.

Design and operationalize AI systems on Google Cloud for defense programs, leading the delivery of secure AI/ML solutions and mentoring engineering teams.