About the Role
We’re building a runtime code sensor that operates where most tools don’t: inside running applications. Our goal is to give engineers and AI agents real-time, high-fidelity visibility into how code actually behaves in production – under real load, real traffic, and real failures.
This role blends deep systems engineering with applied research. You’ll dive into runtime internals, explore undocumented behavior, design low-overhead instrumentation, and turn research insights into production-grade components that safely run in customer environments. One day you might analyze GC or JIT behavior; the next, design tracing mechanisms that survive real-world distributed systems.
If you get excited about runtime internals, enjoy breaking (and fixing) complex systems, think like both a researcher and a production engineer, and care deeply about performance, safety, and correctness – you’ll feel right at home here. This is a hands-on, high-impact role for engineers who want to ship technology that engineers actually trust to run in their most critical services.
Hard Skills / Experience
- 5+ years of hands-on research or development roles.
- Deep expertise in at least one runtime (Node.js, Python, or Java/JVM), including understanding of internals (event loop, GC, tracing hooks, bytecode/JIT, etc.).
- Hands-on experience building in-process production components (SDKs, agents, profilers, monitoring/security tools) that must be safe, stable, and backward-compatible.
- Strong performance engineering skills – profiling CPU/memory, avoiding overhead, understanding how instrumentation affects runtime behavior.
- Defensive engineering mindset – experience designing systems that fail-open, degrade gracefully, protect the host application, and never introduce instability.
- Track record debugging production issues (latency, memory leaks, regressions, deadlocks) in real-world distributed systems.
- Solid understanding of modern backend architectures – experience with microservices, distributed systems, async and event-driven patterns, containers/orchestration (Docker/K8s), cloud runtimes, and the performance or reliability challenges they introduce.
- Proven ability to ship stable, resilient, maintainable systems in production.
Engineering Excellence / Mindset
- Ability to anticipate technical risks, identify bottlenecks, and drive long-term engineering improvements.
- Takes ownership of code quality, documentation, reliability, and observability.
- Comfortable working with product teams to balance technical trade-offs with user and business needs.
- Autonomous and proactive; capable of mentoring others or leading technical initiatives.
Bonus Points
- Background in security agents, observability tools, or other components deployed directly into customer environments.
- Experience with APM agents, JVM agents, Python tracing, V8 internals, or other instrumentation/profiling frameworks.
- Experience with telemetry systems (metrics, tracing, logging) including batching, rate-limiting, and safe data collection.
- Familiarity with sampling techniques, bytecode manipulation, eBPF, or low-overhead tracing.
- Exposure to safety-critical or high-throughput environments where reliability and minimal overhead are mandatory.
- Contributions to open-source instrumentation, tracing, or internals-related projects.
Requirements
- This is a full-time on-site position located in Tel Aviv.
- Ability to thrive in a dynamic, fast-paced startup environment is essential.