Software Engineer - AI Solutions

We are seeking a creative and talented Software Engineer to join our team. In this role, you will be responsible for developing next-generation AI-based tools to revolutionize the efficiency and productivity of our R&D processes.

You will join a team dedicated to solving complex engineering challenges by integrating intelligent solutions into our workflow. You will collaborate with internal AI initiatives, leverage NVIDIA’s cutting-edge internal AI infrastructure, and utilize both internal and external models to build the engineering ecosystem of the future. If you are a developer with a strong Computer Science foundation and a deep passion for Generative AI and Large Language Models (LLMs), we encourage you to apply.

What You Will Be Doing

• Design and develop AI-powered software tools and automation aimed at dramatically improving engineering productivity.
• Implement advanced AI workflows, such as Retrieval-Augmented Generation (RAG) and intelligent assistants, to solve real-world development problems.
• Collaborate with cross-functional teams and internal AI initiatives to identify bottlenecks and translate them into scalable solutions.
• Work hands-on with internal and external AI models (LLMs), orchestrating them to deliver high-quality, reliable outputs.
• Stay up-to-date with the rapidly evolving landscape of AI to continuously optimize our tools and methodologies.
  
  

• B.Sc. in Computer Science, Software Engineering, or a related field.
• 3+ years of experience in software development with strong proficiency in Python.
• Proven experience with AI application frameworks (e.g., LangChain) and vector databases.
• Solid understanding of Generative AI concepts, including RAG, Embeddings, and Prompt Engineering.
• Strong problem-solving skills and the ability to work effectively in a collaborative environment.
• We are a multi-language team, thus your outstanding verbal English skills are important.
  
  

• Experience building autonomous agents or complex reasoning chains.
• Experience taking LLM-based solutions from proof-of-concept to production.
• Experience with API integration and developing backend services (e.g., Flask, FastAPI).
• Background in DevOps practices, CI/CD pipelines, or Linux environments.