Remote Software engineering Jobs • LLMs

Reprogram how humans and intelligent systems grow together in CloudWalk’s experimental playground where People, AI, and Data collide. Design and prototype AI copilots, LLM-powered flows, and smart systems that boost how we learn, hire, evolve, and collaborate. Dive into People data and make it speak through dashboards, bots, agents, and stories. Build experimental tools that rethink how we run people ops. Prototype fast and iterate.

You will play a critical role in building agents, automating internal tools to improve efficiency, developing AI-powered applications to meet the needs of internal stakeholders and customers, and prototyping/experimentation. You’ll have a unique opportunity to work closely with leadership, help develop our AI strategy, and tackle innovative projects.

This hands-on technical role spans Generative AI (GenAI), traditional Machine Learning (ML), and early-stage Data Science. You’ll play a critical part in delivering high-impact AI solutions, establishing best practices, and supporting the development of our AI capabilities across the business. You will work across the full AI lifecycle - from prototype to production - and contribute to platform development, MLOps/LLMOps infrastructure, and applied data science.

Contribute to building and maintaining highly reliable systems that serve millions daily. Collaborate within autonomous squads to drive innovation & achieve user impact. Take end-to-end ownership of services, from ideation to delivery and maintenance. Help define and uphold operational excellence standards across Prismic. Mentor and learn from a vibrant engineering community.

Play a pivotal role in Coinbase's transformation, leveraging cutting-edge AI models, frameworks, and tools, as well as diverse and extensive data sources—including blockchain data. Focus on lowering the barriers to cryptocurrency adoption while shaping the future of AI-powered interactions. Enhance recommendations, chatbots, and other intelligent features to make products more intuitive, accessible, and user-friendly.

As a Staff Machine Learning Engineer, you will lead the development of next-generation AI-driven features, transforming the audit and advisory industry through cutting-edge generative AI solutions. You’ll focus on applying advanced ML and LLMs to solve complex problems for our customers, while guiding the technical direction of our ML team in a high-growth startup environment. This role is both strategic and hands-on, setting best practices for our generative AI efforts.

Lead the design and deployment of intelligent, autonomous systems, leveraging generative AI, multi-agent frameworks, and cloud-native AI infrastructure. Architect and implement agentic AI systems integrating LLMs, planning modules, memory, and tool-use capabilities. Design and deploy multi-agent orchestration frameworks for enterprise use cases. Build and manage cloud-native AI pipelines using both AWS and Azure AI services.

We’re looking for a Staff Engineer, AI to join our Engineering Excellence team and play a strategic leadership role across product, platform, and architecture. You’ll work closely with our high-performing Formless team to design, build, and scale AI capabilities that are core—not additive—to our platform. This role is both deeply technical and highly strategic, requiring a mix of hands-on engineering, architectural vision, and cross-functional collaboration.

Lead a new cross-functional team at Rasa, reporting directly to the Director of Engineering. Work closely with a product manager and designer to shape, deliver, and iterate on features that push the boundaries of conversational AI. Grow an empowered, high-performing engineering team that thrives in a fast-moving, remote-first environment.

You will mainly be responsible for developing a new product utilizing machine learning techniques and generative AI from a proof of concept into a releasable product. Responsibilities include creating effective prompts to maximize the quality of the output from LLMs, building machine learning models, working with engineers and product leads, and creating PoC applications to validate ideas.