Staff Software Engineer (Gen AI)

Job Description:

DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future.

We are seeking an experienced Staff Software Engineer to join our GenAI team. The team is responsible for developing the core services and infrastructure that power DataRobot's Generative AI offerings, enabling our customers to build, deploy, and manage cutting-edge AI solutions. This role will involve designing and implementing scalable backend systems that support the full lifecycle of large language models (LLMs), from serving to monitoring and management. You will work on an internal platform to empower practitioners to deliver both predictive and generative AI.

Key Responsibilities:

• Lead the technical design and implementation of projects, driving them from conception to completion.
• Mentor other engineers, provide constructive feedback in code reviews, and promote a culture of team growth.
• Design and build robust, scalable application-level software and internal services that support GenAI products.
• Work on systems to ensure microservices are secure, performant, and can be deployed safely.
• Collaborate with product managers and data scientists to gather requirements and provide technical feedback on complexity and approaches.
• Engage in engineering on-call escalated support for services owned by the team.
• Troubleshoot complex production environments at the application and DB level.
  

Knowledge, Skills & Abilities:

• 8+ years of proven experience writing high-quality code in a collaborative environment using Python.
• Strong Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem-solving, and complexity analysis.
• Deep experience with automated testing and test-driven development.
• Demonstrable knowledge of software architecture for large systems and real-world experience decoupling monolithic software into smaller reusable components.
• Expert proficiency in Kubernetes architecture and operations, with hands-on experience building and running software systems on Kubernetes clusters in production.
• Hands-on experience with infrastructure provisioning and configuration using Infrastructure as Code (IaC) principles.
• Proven track record of defining technical direction and influencing decisions without formal authority.
• Ability to solve ambiguous, open-ended challenges and influence technical direction across multiple teams.
• Great communication skills, with an ability to work in teams, share knowledge, and write documentation.