Senior AI Engineer
Build and ship AI-powered observability features using LLMs and agent workflows to help users detect, triage, and resolve incidents. Requires strong production software engineering experience plus practical GenAI 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 related tooling: Kubernetes, Docker, Terraform or similar for deployments.
- Familiarity with model fine-tuning techniques.
- Experience building observability tooling.
Compensation & Rewards
- Base compensation range: USD 127,651 - USD 203,867.
- All roles include Restricted Stock Units (RSUs).
- Benefits include equity, bonus (if applicable), and other benefits.
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