Solutions Engineer

Hud enables top engineering teams to monitor and resolve production issues faster and with minimal manual effort. By automatically collecting the full context required to debug and fix issues, Hud allows engineers (and AI agents) to move seamlessly from detection to resolution.

Our SDK captures 100% of function-level performance data and dynamically gathers deeper context when issues arise—empowering intelligent agents to reason about and solve production problems.

Hud is trusted by leading engineering teams such as monday.com, Drata, Axonius, and Cyera. We are a fast-growing, AI-native startup that moves quickly and ships continuously.

This is a hybrid role combining hands-on software engineering, deep production debugging, and direct customer engagement.

You will work directly inside customer production systems, integrating Hud’s SDK, solving real-world issues, and shaping how our product is used in practice. At the same time, you will translate field learnings into scalable product improvements and reusable systems.

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 behaves in production—under real load, real traffic, and real failures.

This role blends deep systems engineering with applied, real-world problem solving. You’ll navigate complex production environments, explore runtime behavior, and design low-overhead solutions that are safe, reliable, and production-ready.

If you enjoy breaking (and fixing) complex systems, working closely with customers, and building tools that engineers trust in their most critical services—this role is for you.

• 6+ years of experience in software engineering, solutions engineering, field engineering, or technical leadership roles

• Strong backend engineering fundamentals and production debugging skills

• Deep expertise in at least one runtime: Node.js / TypeScript, Python, or Java (JVM)

• Experience working within real production systems, including troubleshooting latency, memory issues, regressions, and distributed system failures

• Strong understanding of modern backend architectures:

  • Microservices and distributed systems

  • Async and event-driven systems

  • Containers and orchestration (Docker, Kubernetes)

  • Cloud environments and production reliability challenges

• Hands-on experience building or integrating SDKs, devtools, or production-facing components

• Strong performance engineering skills (CPU/memory profiling, minimizing overhead)

• Ability to design safe, stable, and resilient systems that operate inside customer environments

• Full-time, on-site role in Tel Aviv

• Ability to thrive in a fast-paced, dynamic startup environment

• Strong ownership mindset: code quality, reliability, observability, and documentation

• Bias to action—build fixes, tools, and workarounds rather than only providing guidance

• Ability to anticipate risks, identify bottlenecks, and drive long-term improvements

• Comfortable balancing technical trade-offs with product and customer needs

• Autonomous, proactive, and capable of leading technical initiatives

• Strong communication skills and comfort in customer-facing environments

• Experience with observability, performance monitoring, or developer tooling

• Background in SDKs, instrumentation, or in-process production components

• Experience designing AI-assisted SDLC workflows (LLM agents, evaluations, guardrails, human-in-the-loop systems)

• Familiarity with runtime internals (e.g., event loop, GC, JIT, tracing hooks)

• Experience with APM agents, tracing systems, or telemetry pipelines

• Exposure to low-overhead instrumentation techniques (sampling, bytecode manipulation, eBPF)

• Previous customer-facing technical roles such as FDE, Solutions Engineering, or Sales Engineering

• Own technical execution end-to-end across customer engagements and internal tooling

• Integrate Hud’s SDK into complex production systems across different environments and stacks

• Debug real production issues (performance, reliability, edge cases) and demonstrate Hud’s value

• Build and ship code (primarily in FDE tooling and internal codebases)

• Design and implement repeatable agentic workflows, where production signals power automated workflows across the SDLC

• Create reusable assets such as playbooks, runbooks, templates, reference architectures, and demo environments

• Turn recurring customer pain points into scalable solutions and product improvements

• Collaborate closely with Product and Engineering to translate field insights into features and capabilities

• Lead technical customer interactions, including calls, debugging sessions, and written communication

• High-impact role – Play a critical role in how customers adopt and extract value from Hud

• Shape the product – Turn real-world production challenges into product capabilities

• Build from zero to one – Define workflows, playbooks, and systems for this function

• Work at the frontier of AI + production systems – Help define how production signals power agentic workflows

• Fast-moving environment – Ship constantly, iterate quickly, and take real ownership