דרושים » אבטחת איכות QA » Low-level Quality Lead

As a Senior Low-level Software in our Sensor team, you will design, implement, and optimize cutting-edge software that runs within our clients' environments and monitors their applications accurately and efficiently. Youll have the opportunity to tackle complex technological challenges, research new technologies and build innovative solutions in the Linux system realm. In particular:

Design, Plan and implement efficient and reusable code that drives complex applications
Research innovative solutions that set our Application Security approach apart
Optimize performance and resource consumption in challenging environments
Lead complex projects in close collaboration with Product Managers and other Software Engineers
Interface and collaborate with other R&D teams to deliver end-to-end solutions

We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

We are looking for a hands-on QA & Automation Team Lead who embodies ambition and positivity.
Someone who can passionately take ownership of quality across our high-level software, lead by example, and collaborate effectively with remote teams to not only meet but exceed our objectives and fulfill the evolving needs of our expanding customer base.
Responsibilities:
- Own the quality and test automation strategy across QM's high-level software, including our SDKs, APIs, user-facing tools, and the services around them.
- Lead a team of QA and automation engineers - setting technical direction, mentoring, and growing the team's capabilities while staying hands-on.
- Design, build, and maintain robust automation frameworks and the test suites that run within our CI flows, validating functionality, performance, and stability.
- Define test plans, coverage goals, and quality gates in close partnership with R&D, architecture, and product teams.
- Partner with DevOps to integrate test suites into the CI/CD pipelines they own, ensuring quality gates are well-defined and effective.
- Own Tier 2 customer support for software issues - investigating escalations, reproducing and diagnosing problems, driving them to resolution, and feeding insights back into test coverage and product quality.
- Drive root-cause analysis and continuous improvement of test reliability, flakiness, and release confidence.
- Establish metrics and reporting that give the organization clear, actionable visibility into product quality and release readiness.

We are looking for a hands-on QA & Automation Team Lead who embodies ambition and positivity.

Someone who can passionately take ownership of quality across our high-level software, lead by example, and collaborate effectively with remote teams to not only meet but exceed our objectives and fulfill the evolving needs of our expanding customer base.

Responsibilities:

- Own the quality and test automation strategy across QM's high-level software, including our SDKs, APIs, user-facing tools, and the services around them.

- Lead a team of QA and automation engineers - setting technical direction, mentoring, and growing the team's capabilities while staying hands-on.

- Design, build, and maintain robust automation frameworks and the test suites that run within our CI flows, validating functionality, performance, and stability.

- Define test plans, coverage goals, and quality gates in close partnership with R&D, architecture, and product teams.

- Partner with DevOps to integrate test suites into the CI/CD pipelines they own, ensuring quality gates are well-defined and effective.

- Own Tier 2 customer support for software issues - investigating escalations, reproducing and diagnosing problems, driving them to resolution, and feeding insights back into test coverage and product quality.

- Drive root-cause analysis and continuous improvement of test reliability, flakiness, and release confidence.

- Establish metrics and reporting that give the organization clear, actionable visibility into product quality and release readiness.

Were looking for a Low-Level Developer to join the team - someone who loves working close to the kernel, cares deeply about performance, and wants their code measured in nanoseconds and bytes.
What You'll Do:
Design and build the in-cluster sensor that powers groundcover's observability platform
Write low-overhead, high-performance instrumentation using eBPF and Go
Tackle hard problems in Linux internals, networking, and protocol parsing
Push the boundaries of what can be observed without modifying customer code
Ensure the sensor runs reliably across a huge variety of kernels, distros, and Kubernetes setups
Collaborate with backend, infrastructure, and product teams to ship features end to end

Were looking for a Senior Automation Engineer to join our Automation team. As a member of this team, you will be responsible for the design, implementation, and maintenance of automated tests and infrastructure using our Java-based framework. Our Automated tests cover various aspects of the security product, including complex networking topology, traffic, security rules, Users authentication scenarios.


Responsibilities

Design, develop, and maintain automated tests for complex, multi-layered systems using our Java-based framework
Drive initiatives to enhance automation infrastructure and tools to support seamless development and testing workflows.
Define, build, and maintain automation infrastructure, frameworks, and reusable libraries, to improve test execution reliability, reduce flakiness, shorten feedback loops, and increase confidence in automation results.
Evaluate and integrate AI-driven solutions into the automation workflow, improving productivity, reliability, and insight generation
Leverage AI-based tools and techniques to enhance test automation, including test generation, failure analysis, and optimization of test coverage and execution
Enable QA automation engineers and developers with reusable components, templates, tools, dashboards, CI/CD integrations, and best practices.
Translate automation data into actionable insights for automation engineers, developers, product teams.
Identify gaps and develop tools and solutions to improve automation efficiency, stability, and scalability
Collaborate with development, product, and cross-team automation groups to ensure high-quality delivery and unified standards

We're looking for a DevOps / Platform Engineer to own our infrastructure end to end- both sides of it.
Side one is our multi-tenant SaaS on AWS: you build it, you run it, you keep it fast, secure, and up. Side two is the part that makes this role unusual - our enterprise customers deploy Avon AI inside their cloud (and sometimes fully air-gapped, on-prem environments). You'll own that too: packaging the platform, running the installation with the customer's infrastructure and security teams, and being the person on the call when their environment doesn't look like anyone's reference architecture.
This is a customer-facing engineering role. You'll be in rooms with enterprise IT, security, and platform teams- walking them through our architecture, answering security review questions, and unblocking deployments. If you want a pure behind-the-scenes infra job, this isn't it. If you like owning infrastructure and being the trusted technical voice in front of a customer, read on.
You'll be our first dedicated DevOps hire, which means you inherit real systems in production and a lot of room to shape how they evolve.
Key Responsibilities
EKS, networking, data stores, CI/CD, cost, and uptime. Build and evolve it with Infrastructure as Code.
Maintain and improve our Helm charts and container distribution so Avon AI installs cleanly in a customer's Kubernetes cluster.
Plan and execute installations in customers' private clouds and on-prem/air-gapped environments, working hands-on with their infrastructure teams from kickoff through go-live.
Support security reviews and architecture discussions, and translate enterprise IT constraints back into our roadmap.
IAM, network segmentation, secrets management, WAF, and the controls enterprise customers audit us on.
Metrics, logs, tracing, and alerting for our SaaS, and self-contained monitoring for customers who won't ship telemetry outside their network.
CI/CD pipelines, ephemeral PR sandboxes, release automation, and local development so engineers ship quickly and safely.
For our SaaS tenants and for deployed customer installations, including on-call ownership of what you build.

Were looking for a senior engineer who is ready to move beyond traditional software development and take full ownership of product delivery.

This is not a classic backend engineering role. You will work directly with Product to turn ideas and requirements into production-ready solutions, make the technical decisions, and use AI coding agents as a core part of your engineering workflow.

You will own the outcome, not just the code. AI-generated code is your code, and you are accountable for its quality, security, performance, and maintainability.


Own product features end-to-end, from requirements through production and monitoring.
Work with Product to translate business problems into clear technical solutions and execution plans.
Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations.
Use AI coding agents to accelerate implementation, testing, debugging, and automation.
Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability.
Make independent technical decisions and communicate architectural trade-offs clearly.
Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature.
Investigate and solve complex production and performance issues.
Continuously improve how we build, test, and ship software using AI-native development practices.

We are looking for a Senior AI Ops Engineer to join our AIOps team and help build the AI-powered platforms, agents, and workflows that enable engineering teams across our company.
This is a hands-on role for someone who can take AI solutions from idea to production, build the infrastructure around them, and create the observability needed to understand and improve how they behave in the real world.
Job responsibilities
Build and operate production-grade AI agents, AI-enabled tools, and workflows that empower developers and operational teams.
Design agentic systems using frameworks such as LangGraph, LangChain, and Supervisor, including RAG, MCP integrations, tool calling, and guardrails.
Build and evolve an AI SDLC harness that helps teams plan, implement, validate, govern, and safely deliver AI-assisted software changes.
Lead AI observability with Langfuse and OpenTelemetry, including tracing, evaluations, quality measurement, and cost analysis.
Build automated evaluation frameworks, including LLM-as-a-judge, to improve the reliability and quality of AI systems.
Design and maintain the infrastructure, CI/CD pipelines, GitOps workflows, and security controls that support AI services.
Develop internal developer tooling and automation that removes friction across the engineering organization.
Partner with engineering and product teams to turn real operational challenges into scalable AI-powered solutions.