Staff Engineer - Observability

Requirements

• 10+ years of experience in software, systems, or platform engineering, including 3+ years in a similar technical leadership role within the observability or large-scale distributed data systems domain.
• Distributed Systems & Storage Expertise: Deep, hands-on experience designing, scaling, and operating core telemetry data engines (such as distributed search databases, time-series metrics systems, high-performance logging architectures) at a multi-petabyte scale.
• AI-Ready Telemetry Design: Practical understanding of structuring, schema-enforcing, and cleaning high-volume telemetry streams for optimized consumption by LLMs, semantic search engines, and RAG pipelines.
• Telemetry Standardization: Experience adopting industry-standard telemetry collection frameworks (such as OpenTelemetry) and implementing SLO-driven alert governance.
• Software Engineering Mindset: Strong proficiency in software development (ideally in Go, Java, or Python) with a history of building production-grade, automated tooling, and robust real-time data ingestion pipelines.
• Kubernetes & Infrastructure Fluency: Extensive experience operating and troubleshooting high-throughput workloads on production Kubernetes (both on-prem and cloud) alongside a solid understanding of system-level performance tuning (networking, storage, and operating system limits).
• Influence and Collaboration: Exceptional communication and system-design skills, with a proven ability to translate complex technical trade-offs for diverse stakeholders, align multiple engineering teams around a unified technical vision, and mentor and upskill engineers to elevate domain-wide technical execution.

What you'll be doing

• Drive Strategic Architecture: Architect and execute the technical strategy for the observability platform aligning long-term product vision with resilient, highly scalable engineering designs.
• Scale the Data Foundation: Lead the architectural revamp of petabyte-scale search, logging, and metrics systems, guiding the transition to highly optimized, regionalized, and multi-tenant telemetry pipelines.
• Enable Intelligent Observability: Architect APIs, secure interfaces, and integration protocols connecting the data foundation to AI agents for real-time diagnostics and conversational query tools.
• Establish Resilient Topologies: Deconstruct monolithic monitoring setups into isolated, high-availability architectures to enhance global operational stability.
• Simplify Developer Experience: Collaborate with product and engineering teams to design self-service developer tooling leveraging GitOps-driven configuration models, automated schema enforcement, and intuitive management.
• Technical Leadership & Guidance: Provide technical direction across the observability domain, champion design reviews, and guide engineers through complex distributed systems challenges.
• Advocate Company-Wide: Act as a technical advocate for the domain, aligning telemetry capabilities with broader organizational needs, and promoting modern observability standards.

Nice to have

• Agentic & LLM Integration: Experience with Model Context Protocol (MCP) or similar standards for platform data exposure to AI agents and SRE assistants.
• Intelligent Diagnostics: Experience with automated anomaly detection, conversational AI querying interfaces, or continuous profiling platforms.
• Governance at Scale: Familiarity with automated multi-tenant isolation, capacity management, and cost-attribution frameworks for large-scale enterprise developer platforms.