Salesforce Senior Fullstack Engineer - AI Research ...

## About the RoleIn this role, you will play a pivotal part in accelerating the work of our researchers and data collection teams by building tools and infrastructure that streamline the end-to-end process of collecting, annotating, and managing AI agent data. You will collaborate closely with researchers and data scientists to transform early research ideas into robust incubation products, contributing to both backend services and frontend interfaces that support internal workflows and pilot customer deployments. By implementing state-of-the-art research into production-quality demo prototypes, you will help bridge the gap between cutting-edge innovation and real-world impact—bringing research to life in ways that inform product direction and deliver tangible value to the broader AI ecosystem.## QualificationsBachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. 5+ years of professional experience as a fullstack engineer or software developer. Experience building internal tools or UIs for data labeling, annotation, or human-in-the-loop workflows. Proficiency in building and integrating RESTful APIs, with experience using modern JavaScript frameworks such as React. Strong knowledge of object-oriented programming and fluency in at least one core language (e.g., Python, Java, JavaScript, C++). High proficiency in at least one backend web framework (e.g., Node.js with Express, Python with Flask/FastAPI/Django) Solid understanding of frontend technologies including JavaScript, CSS, HTML5, and asynchronous communication (e.g., JSON, AJAX). Familiarity with database design and query optimization using relational databases (e.g., PostgreSQL, MySQL). Experience with automated testing frameworks for unit, integration, and end-to-end testing. Excellent communication and collaboration skills, especially when working with cross-functional teams including researchers and data scientists Preferred Skills: Experience working with LLMs, agent frameworks, or retrieval-augmented generation (RAG) systems. Familiarity with Python-based AI research tooling (e.g., LangChain, LlamaIndex, Hugging Face Transformers). Experience designing, maintaining, and scaling structured or semi-structured data pipelines. Experience deploying fullstack applications using Docker and cloud platforms (e.g., AWS, GCP, or Azure). Demonstrated ability to turn research papers or models into interactive prototypes or product-ready demos. Experience building robust internal systems and user-facing tools for research or experimentation. Familiarity with Agile development processes and a strong bias toward rapid iteration and continuous improvement.## ResponsibilitiesBuild full-stack tools and infrastructure that streamline end-to-end collection, annotation, and management of AI-agent data. Collaborate closely with researchers and data scientists to turn early research ideas into robust incubation products. Develop backend services (e.g., RESTful APIs) and frontend interfaces (e.g., React) that support internal workflows and pilot customer deployments. Implement state-of-the-art research into production-quality demo prototypes that inform product direction. Create and maintain internal UIs for human-in-the-loop labeling/annotation workflows. Integrate, optimize, and maintain data storage layers (e.g., relational databases) to support research and experimentation. Establish quality through automated unit, integration, and end-to-end testing for services and UIs. Collaborate across functions (engineering, research, data) with clear communication and rapid iteration. Work with LLMs/agent frameworks/RAG systems and Python-based AI tooling to accelerate research. Design and operate containerized/cloud deployments (Docker; AWS/GCP/Azure) for internal apps and prototypes. #J-18808-Ljbffr

Created: 2025-09-18