דרושים » תוכנה » Senior Full Stack Developer

Required Full Stack Developer
As a Full Stack Developer, you will:
Develop the next generation features of the main backend services of various Company products
Design and develop high-volume, low-latency and scalable product
Partner closely with product managers, project managers and architects to align technical execution with business goals
Own features from requirements through design, implementation, testing, deployment and production support
Write well-designed, testable (unit/integration/component testing), secured and efficient code

Key Responsibilities:
Design, develop, and evolve core full-stack features, with an emphasis on scalability, performance, and maintainability.
Lead complex technical initiatives from concept through production, making architectural decisions that drive long-term impact.
Take end-to-end responsibility for production systems, including monitoring, troubleshooting, performance optimization, and incident resolution.
Maintain high engineering standards through code reviews, testing, documentation, and best practices.
Continuously evaluate and adopt modern development tools to improve developer productivity and system quality.
Support and mentor other engineers as needed, sharing knowledge and contributing to team growth.

We are looking for a Senior Full-Stack Engineer to join us in building a new production-grade system for the enterprise from scratch. This is a role for an experienced engineer who knows what it takes to bring such a system to production end to end, and treats AI as a core part of the toolkit, both as a force multiplier in how they build and as a first-class capability in what they build. In this role, you will be a key member of our growing team of developers, data scientists, and analysts. You will build a complex, data-intensive system that is powered by LLMs and intelligent agents, and provides a delightful experience to our users.
Responsibilities:
Help architect and build a new AI-native system from the ground up, making foundational design and technology decisions.
Own features end to end, from design through production, deployment, and maintenance.
Build AI-powered product features - integrate LLMs, RAG pipelines, agents, and ML models into production with attention to performance, reliability, guardrails, and observability.
Work AI-natively - use AI coding assistants and agentic tools to accelerate design, implementation, testing, and review, while owning correctness and quality.
Establish and improve the platforms, patterns, and tooling the team builds on.