AI Engineer

Writer Writer · AI Frontier · San Francisco, CA · Engineering, product & design

AI Engineer role focused on building and deploying scalable AI applications, intelligent agents, and AI-powered features for enterprise clients. The role involves architecting, developing, and integrating these solutions into an end-to-end platform, collaborating with research and product teams, and contributing to the evaluation of new AI technologies. Emphasis on production deployment, scalability, and responsible AI practices.

What you'd actually do

  1. Architect, develop, and deploy high-performance, scalable AI applications into production environments, ensuring robust integrations with our end-to-end platform.
  2. Drive the development of intelligent agents and AI-powered features, translating complex research into practical, impactful solutions for our customers.
  3. Collaborate closely with research scientists, data scientists, and product managers to define technical requirements and deliver features that address critical business needs.
  4. Contribute to the research and evaluation of emerging AI technologies, frameworks, and tools to maintain WRITER's leadership in the enterprise generative AI space.
  5. Champion responsible AI practices, including bias detection, explainability, and safety alignment, making sure our AI is trustworthy and ethical.

Skills

Required

  • 5+ years of professional experience building and deploying machine learning or AI systems in a production environment.
  • Proficiency in Python and experience with relevant AI/ML frameworks such as PyTorch, TensorFlow, or JAX.
  • A strong foundation in machine learning principles, deep learning architectures, and natural language processing, particularly with large language models.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools for managing the AI lifecycle.
  • Demonstrated ability to write clean, efficient, and well-tested code for scalable software systems.
  • Exceptional problem-solving skills and a passion for tackling complex technical challenges with creative AI solutions.

Nice to have

  • Connect by collaborating seamlessly across diverse teams
  • Challenge the status quo to innovate
  • Own your projects with a commitment to impact and excellence

What the JD emphasized

  • building and deploying machine learning or AI systems in a production environment
  • scalable AI applications
  • intelligent agents
  • AI-powered features
  • enterprise generative AI space
  • responsible AI practices

Other signals

  • building and deploying AI agents
  • grounded in their company's data
  • enterprise-grade LLMs
  • AI-powered work
  • superintelligence