דרושים » תוכנה » מפתח/ת JAVA

A fast-growing, well-funded technology company in the cybersecurity / identity domain is looking for a Backend Team Lead to join a high-impact engineering team.
This is a hands-on leadership role combining team management, architectural ownership, and active development. You will lead a mixed-seniority team while driving the design and scalability of a complex, cloud-based platform.
What Youll Do:
Lead, mentor, and grow a team of backend engineers (junior to senior)
Stay hands-on with development using Java (Spring Boot), Go, and Python
Own backend architecture, system design, and technical direction
Lead a new Python-based initiative, setting standards and best practices
Drive code quality, testing, and maintainability
Collaborate closely with Product, Frontend, QA, and DevOps
Take ownership of delivery, execution, and team velocity

we are seeking a Senior Engineer for Cloud Security Product Group.

Were extending mission of stopping breaches into the public cloud and cloud-native workloads. CrowdStrikes product offering will give customers the ability to monitor and track their cloud-native workloads as well as hardening and protecting them against attacks prior to deployment. This offering will help with defending against potential adversary activities involving cloud-native resources. When coupled with Falcon, CrowdStrikes endpoint security offering, our CSPG offering will provide a more comprehensive perspective on how the adversary is targeting key customer infrastructure. Our ultimate goal is to provide a single platform for securing the entire lifecycle of cloud workloads and cloud security posture.

What You'll Do:

Lead backend engineering efforts from rapid prototypes to large-scale applications across CrowdStrike products

Leverage and build cloud-based systems to detect targeted attacks and automate cyber threat intelligence production at a global scale

Brainstorm, define and build collaboratively with members across multiple teams

Work in a startup-like environment with a small fast-moving team

Be mentored and mentor other developers on backend, and data storage technologies and our system

Constantly re-evaluate our product to improve architecture, knowledge models, user experience, performance and stability

Be given the autonomy to own your work in a high trust environment

In this role you'll design and build features that shape how customers discover products - tailored to their preferences, helping them find exactly what they need, even before they know they need it. We're defining how LLMs integrate into real-time personalization, how noisy behavioral signals become durable customer understanding, and how AI-powered experiences ship reliably at scale. You'll work across multiple technical teams, ship iteratively, and see your work in the hands of customers quickly. This organization values experimentation, moves fast, and gives engineers real ownership over what they build.

We are looking for a Software Development Engineer with sound technical judgment and a bias for action who takes ownership of problems end to end, communicates clearly, and cares about operational excellence - not just launching features, but making sure they hold up at scale. Someone who naturally raises the bar for the team: mentoring junior developers, advocating engineering best practices, and thinking beyond the immediate sprint.

Key job responsibilities
- Design, build, test, and operate production AI features used by multiple teams and operating in our scale.
- Deliver end-to-end solutions with focus on maintainability, scalability, performance, and reliability.
- Collaborate with Product and Science to define experiences, run experiments, and iterate based on data.
- Build AI-powered experiences including personalized recommendations, relevance explanations, and knowledge-driven features using LLMs and generative AI.
- Define and implement measurement strategies including analytics events and experiment configurations to track engagement and retention.
- Navigate ambiguity and make sound technical decisions in a problem space where established patterns don't always apply.