Principal AI Engineer

OutSystemsSan Francisco, CA
11dHybrid

About The Position

Join OutSystems, a global leader in software innovation, and contribute to a truly unique and evolving global culture. As a Principal AI Engineer, you will be crucial in bridging research and production, deploying cutting-edge AI across the full application lifecycle, from design through development to production. Work with other AI Engineers to transform state-of-the-art models into robust, scalable, and efficient software development experiences. Your expertise will directly enhance how developers interact with our platform, making complex tasks intuitive and accessible.

Requirements

  • Proven ability to design, build, and ship complex, data-intensive, and scalable systems in a real-world setting.
  • Strong problem-solving skills and programming proficiency, including the ability to architect and implement end-to-end solutions (from data processing and model development to deployment and monitoring).
  • Expertise in Python is required; experience with C# is valued.
  • Exhibit creativity, ambition, curiosity, resourcefulness, and innovation.

Nice To Haves

  • M.Sc. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field (e.g., Electrical Engineering, Physics, Statistics).
  • 10+ years of hands-on professional experience in applied AI/ML roles with a proven record of delivering impactful solutions.
  • Demonstrable experience deploying and managing Large Language Models (LLMs) in production environments.

Responsibilities

  • Design and architect ML/AI systems, collaborating cross-functionally with multiple stakeholders.
  • Contribute to the architecture of OutSystems' AI platform and services.
  • Partner with Research Scientists to design, prototype, and implement state-of-the-art AI models and algorithms, ensuring production optimization for scale and performance.
  • Develop and implement highly available, fault-tolerant systems for serving sophisticated AI models, with a focus on reliability, efficiency, and MLOps best practices.
  • Define data collection strategies and feedback loops to enable continuous learning and improvement of our AI capabilities and product offerings.
  • Guide, mentor, and elevate the technical capabilities of other AI Engineers, championing best practices in design, implementation, and AI development.
  • Maintain deep knowledge of the state-of-the-art in AI/ML models, agents, and developer tools, driving the adoption of relevant advancements across the team and company.
  • Collaborate cross-functionally to identify opportunities and enhance our AI products and data infrastructure.
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