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Salary
≈ $112k – $280k per year (Estimated)
Location
Hybrid (Tel Aviv, Israel)
Seniority
Staff · 7+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 27, 2026. First seen by Alion on Oct 25, 2026.

Overview
Company
Impact
Profile match
Sentra is an Israeli company founded in 2021 that secures data in cloud environments. Its platform classifies sensitive data and detects risky access without moving it. The company serves enterprises with large cloud estates.

Description

We are looking for a highly technical, hands-on Quality Engineering Lead to drive product quality through AI-powered automation, intelligent testing, and proactive issue detection.

Your mission is to build and continuously improve automated quality mechanisms that identify bugs, regressions, performance issues, and unexpected system behavior before they impact our customers.

You will leverage AI agents, modern development tools, and engineering automation to make quality an integral and continuous part of our development lifecycle.

This is a senior, hands-on technical leadership role with ownership of the Quality Engineering domain across R&D. You will define the technical direction, lead cross-team initiatives, and establish the foundations for a scalable, AI-driven quality engineering function, with the opportunity to build and lead a dedicated team as the domain evolves.

We are looking for someone who combines strong software engineering expertise, a passion for product quality, and the leadership skills to drive meaningful change across the engineering organization.

Responsibilities

  • Build AI-Powered Quality Agents: Design and implement agents that proactively identify bugs, regressions, and unexpected behavior across our systems.
  • Develop Intelligent Testing Mechanisms: Build automated testing solutions that leverage AI to generate, execute, and maintain meaningful test scenarios.
  • Proactive Issue Detection: Analyze logs, metrics, traces, production behavior, and code changes to identify potential quality issues.
  • Automate Regression Detection: Develop mechanisms that continuously validate system behavior and detect regressions introduced by new releases.
  • Improve Release Confidence: Build automated quality gates and validation mechanisms integrated into CI/CD pipelines.
  • Production Quality Monitoring: Develop intelligent mechanisms that detect functional inconsistencies, data integrity issues, and unexpected production behavior.
  • AI-Assisted Root Cause Analysis: Build tools and agents that investigate detected issues, identify likely causes, and provide actionable findings to engineering teams.
  • Drive Quality Engineering Across R&D: Collaborate with all engineering teams to identify quality gaps, establish best practices, and drive the adoption of AI-powered quality mechanisms throughout the development lifecycle.
  • Technical Leadership & Ownership: Own and lead the Quality Engineering domain across R&D. Define the technical direction, drive cross-team initiatives, establish engineering standards, and mentor engineers working on quality-related solutions.
  • Build and Scale the Quality Engineering Function: Establish the technical foundations, processes, and tools needed to scale quality engineering across the organization, with the potential to build and lead a dedicated team.
  • Own Quality Improvements End-to-End: Independently design, develop, deploy, and maintain quality engineering tools and automation, ensuring measurable improvements in product quality.

Requirements

  • 7+ years of hands-on software engineering, quality engineering, or test infrastructure development experience.
  • Proven technical leadership experience as a Tech Lead, Staff Engineer, or equivalent, with the ability to drive cross-team initiatives and influence engineering practices.
  • Strong programming skills in Python, TypeScript, or similar languages.
  • Extensive experience building automated testing frameworks, quality validation systems, or engineering automation infrastructure.
  • Hands-on experience using LLMs, AI coding tools, or AI agents to solve engineering problems.
  • Strong understanding of backend systems, APIs, distributed architectures, and cloud environments.
  • Experience with CI/CD pipelines, integration testing, and automated regression testing.
  • Strong debugging, troubleshooting, and root cause analysis skills.
  • Ability to define technical direction, mentor engineers, and take ownership of an engineering domain across the organization.
  • Strong communication and collaboration skills, with the ability to work effectively across multiple engineering teams.
  • Ability to independently identify quality gaps and deliver production-ready engineering solutions.

Nice to Have

  • Experience building autonomous AI agents or agent-based testing frameworks.
  • Experience with Claude Code, Cursor, Codex, or similar tools.
  • Experience with Kubernetes, AWS, and microservices architectures.
  • Experience with observability platforms such as Datadog, Groundcover, or Grafana.
  • Experience with performance testing, chaos engineering, or production validation.
  • Familiarity with MCP, LLM tool calling, and agent orchestration.
  • Experience establishing or leading quality engineering initiatives across multiple development teams.
  • Experience building or scaling engineering teams or technical functions.

What Success Looks Like

  • Critical bugs and regressions are detected before reaching customers.
  • Automated quality mechanisms continuously validate product behavior across development and production environments.
  • AI agents reduce manual testing, debugging, and investigation efforts.
  • Engineering teams receive actionable quality findings early in the development cycle.
  • Release confidence increases while maintaining or improving development velocity.
  • Product quality improves through measurable reductions in escaped defects and recurring incidents.
  • Quality engineering becomes a shared, AI-powered capability adopted across all R&D teams.
  • A scalable quality engineering function is established, with clear technical ownership, standards, and long-term direction.

Our Vision

Build an engineering organization where quality is continuously and proactively validated through intelligent automation and AI agents.

  • We believe quality should not depend solely on manual testing or reactive bug fixing. Our goal is to create an AI-driven quality engineering function that continuously identifies problems, prevents regressions, and empowers every engineering team to deliver reliable software faster.
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