Staff-level AI engineer building and shipping LLM/agent-powered observability features that help users detect, triage, and resolve incidents. Requires strong production software engineering experience plus practical GenAI/LLM skills.
175k – 220k
Remote7+ YOEML Engineering
About the role
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 and solutions-oriented.
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.
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