8 open jobs on The Stack list RAG as a key skill. They come from 8 companies in 5 countries, and 8 offer visa sponsorship. All were posted in the last 60 days.
This page lists jobs whose listing names RAG in its key skills. We do not guess skills from the job title.
What you'll do: Design, develop, and maintain LLM-based and agentic applications to support biomedical research projects. Integrate AI components with laboratory tools and databases while applying software engineering best practices.
What they ask for: Requires a bachelor's degree in a technical or scientific field and at least one year of software development experience. Candidates must have hands-on experience with LLMs, agentic systems, and strong Python programming skills.
What you'll do: Develop cutting-edge GenAI solutions and deploy production-grade GenAI applications for customers; serve as a trusted technical advisor across domains; collaborate with product and engineering teams to influence the Databricks roadmap and…
What they ask for: Minimum 4 years of hands-on experience building GenAI applications (RAG, multi-agent systems, Text2SQL, fine-tuning) with tools like HuggingFace, LangChain, and DSPy. Proven experience deploying production ML deployments on AWS, Azure, or…
What you'll do: Design, develop and industrialize AI agents for business workflows using LLMs, RAG and multi-step agent workflows; integrate agents with internal systems via APIs, MCPs/webhooks and data platforms; scale prototypes to secure…
What they ask for: 5+ years in IA/Data Science or ML solution development with end-to-end delivery experience; strong Python and data/IA toolset; proven deployment of AI solutions (LLMs, agents, RAG) and integrations with business systems; familiarity with…
What you'll do: Design, build, and deploy production-grade AI systems powering Mirakl's internal and external products. Design robust AI workflows including agents, tools, memory, retrieval, and guardrails, and ensure reliability and scalability.…
What they ask for: Proven experience building AI-native products at scale; strong background in LLMs, AI agents, and production ML; ability to integrate AI systems with CRM, data platforms, and internal tools; strong cross-functional collaboration and…
What you'll do: The Senior AI Engineer will own the technical delivery of internal machine learning automation projects, from design through deployment. They will integrate agentic AI tools with various business and development platforms while maintaining…
What they ask for: Candidates must have 7+ years of professional Python software development experience and 2+ years of practical experience with GCP. Proficiency in LLM application development, including prompt engineering and RAG, is required along with…
What you'll do: You will design and develop product features that directly impact user workflows while collaborating with design and engineering teams to deliver exceptional experiences. Additionally, you will maintain scalable code, ensure system…
What they ask for: The role requires 6+ years of software or product engineering experience with strong backend proficiency in NodeJS, Postgres, and TypeScript. Candidates should also have experience with LLM application development patterns and be…
What you'll do: You will design and develop techniques to compress Large Language Models using quantum-inspired technologies and build LLM-based applications like RAG and AI agents. Additionally, you will conduct performance evaluations, fine-tune models…
What they ask for: Candidates must hold a degree in a relevant field and possess at least 5 years of hands-on experience in training or fine-tuning deep learning models. Proficiency in Python, transformer libraries, and a strong understanding of GPU…
What you'll do: You will design, build, and operate infrastructure for model access, agent runtimes, and observability. You will also support teams by troubleshooting issues, documenting reusable patterns, and establishing standards for AI-powered tool…
What they ask for: You should have strong software engineering experience with APIs, cloud infrastructure, Kubernetes, and infrastructure-as-code. Familiarity with LLM ecosystems, observability, and a security-conscious approach to system governance is…
