Full Stack Engineer

An innovative technology startup that develops an advanced engineering intelligence and analytics platform designed to measure and optimize the impact of artificial intelligence on software development lifecycles.

By seamlessly integrating with developer environments, project management systems, and operational workflows, the software aggregates multi-source datasets to deliver deep visibility into how AI-generated code affects R&D productivity, code quality, and delivery timelines.

Having secured substantial early-stage venture funding, the company operates with an elite core team out of its central collaborative tech hub.

The company is located in Tel Aviv (train-accessible) and operates on a hybrid model of two days office-based.

Key Responsibilities-

• Writing clean, maintainable, and performance-tuned production code across both client-side and server-side repositories.
• Designing and building scalable RESTful APIs, data-processing workflows, and background services utilizing Python.
• Constructing highly responsive, component-driven UI dashboards in React to map and visualize complex engineering data structures.
• Structuring automated tests, managing deployments, and configuring cloud infrastructure components across AWS and GCP nodes.
• Participating in architectural design sessions, code reviews, and technical scoping inside a fast-paced, product-led startup environment.

Requirements-

• Extensive professional software engineering experience centered on Full Stack production architectures (Mandatory).
• Proven hands-on development experience specializing in backend architectures using Python (Mandatory).
• Strong production-grade experience building responsive web interfaces utilizing React (Mandatory).
• Practical engineering experience deploying, configuring, and optimizing workflows within public Cloud environments (AWS or GCP) (Mandatory).
• Prior professional experience operating within a Startup (SU) environment or a B2B SaaS product company (Mandatory).
• Conceptual understanding or practical development exposure to Generative AI tools, LLM integrations, or machine learning applications is a significant professional advantage.