Staff AI Engineer
Staff AI Engineer building and shipping LLM/agent-powered observability features for incident detection, triage, and resolution. Requires strong production software engineering experience plus practical GenAI/LLM application skills.
What You’ll Be Doing
- Build and deliver AI solutions: Take ownership of developing high-performance AI features to help users detect, triage, and resolve incidents using observability data and tools.
- Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for incident lifecycle management and automated analysis tasks.
- Collaborate cross-functionally: Work with data analysts, product managers, and designers to shape AI-driven product features, including integration of agentic components with internal tools, alerting systems, runbooks, and developer workflows.
- Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
- Effective communication: Work in a highly dynamic and collaborative environment, communicating effectively and contributing across teams.
- Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are innovative, scalable, maintainable, and aligned with real user workflows.
Requirements
- Experience with LLMs, prompt engineering, and building applications powered by GenAI.
- Proven track record of delivering software that made it into production and is actively used by users.
- Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure).
- Experience using observability tools to understand and troubleshoot system behavior.
- Strong engineering skills: Solid experience building production software systems (backend and/or full stack).
- AI experience with a practical mindset: Familiar with AI technologies and frameworks, focused on delivering high-quality real-world solutions.
- Quick iteration and experimentation: Comfortable releasing prototypes, collecting feedback, and iterating pragmatically.
- Proven initiative: Take ownership, drive projects forward, deal with ambiguity, and define scope.
- Collaborative attitude: Communicate effectively with peers, product managers, and designers; open to feedback with a solutions-oriented mindset.
Bonus Points
- Experience building or working with agent frameworks or multi-agent workflows.
- Experience with infrastructure/devops tooling: Kubernetes, Docker, Terraform or similar.
- Familiarity with model fine-tuning techniques.
- Experience building observability tooling.
Compensation & Benefits
- Base compensation range: USD 174,986 - USD 220,000.
- Restricted Stock Units (RSUs) included.
- Bonus (if applicable) and other benefits.
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