Lead Platform UI Engineer, Qdrant
SaaS Platform
Open-source vector search engine for AI
Be an early applicant
Open-source vector search engine for AI
21-100 employees
Be an early applicant
21-100 employees
Company mission
Qdrant's mission is to empower businesses to build and deploy semantic neural search on your data in minutes.
Role
Who you are
- 5+ years of experience in frontend development, with substantial experience owning or co-owning a production React application
- Deep expertise in React, JavaScript/TypeScript, HTML5, and CSS3, including component composition, hooks, and modern patterns
- Solid understanding of web platform fundamentals: JavaScript, DOM, REST APIs, HTTP/HTTP2, caching, browser performance
- Experience with backend technologies (ideally Python or Node.js) and single-page applications (or hybrid architectures)
- Proven track record designing or contributing to frontend architectures, shared component libraries, or design systems
- Strong familiarity with the frontend ecosystem: testing, linting, bundling, error tracking, performance profiling, CI/CD pipelines
- Comfortable debugging frontend–backend interactions, API contracts, and performance issues in production
- Excellent communication skills and ability to collaborate with engineers, product managers, and designers
- Experience providing technical leadership or mentoring to other engineers, even if not in a formal manager role
Desirable
- Familiarity with Python frameworks like Flask or FastAPI
- Familiarity with meta frameworks like Remix, Next.js, and/or libraries like TanStack Router and Query
- Experience with modular, scalable frontend architectures
- Knowledge of OAS, GraphQL and/or WebSockets
- Prior experience working in a SaaS or startup-like environment
What the job involves
- As a Lead Platform UI Engineer with a strong frontend focus and full-stack mindset, you will own the front-of-house experience of Qdrant Cloud as well as the UI platform used by multiple product teams
- Define and evolve the UI platform
- Design and own our frontend architecture for Qdrant Cloud, focusing on modularity, scalability, and performance
- Build and maintain a shared component library / design system in React + TypeScript to be reused across teams and products
- Establish standards for state management, routing, API integration, error handling, and observability in the frontend
- Hands-on frontend development
- Implement complex, high-impact features in React (with modern tooling such as TanStack, OpenAPI, TypeScript, etc.)
- Ship well-structured, testable modules and improve the overall DX (developer experience) of our frontend stack
- Continuously profile and tune frontend performance, bundle size, and runtime behavior
- Cross-functional collaboration & backend integration
- Work closely with backend engineers to shape and optimize APIs, contracts, and data flows for UI needs
- Contribute to Python backend services when necessary to unlock or improve frontend functionality
- Collaborate with Product and Design to turn requirements and UX flows into robust, maintainable implementations
- Technical leadership & mentorship
- Act as the go-to person for frontend and UI platform topics across teams
- Mentor other frontend developers, review critical pull requests, and help establish and enforce coding standards and best practices
- Drive technical decision-making around frontend architecture, libraries, and tooling
- Infrastructure, quality & reliability
- Own key parts of the frontend delivery pipeline: CI/CD, linting, testing, quality gates, error tracking, performance monitoring
- Help define and maintain quality metrics (e.g. core web vitals, error budgets, coverage, build times)
- Ensure our UI stack is secure, observable, and resilient by default
Our take
In many cases, documents may have too few keywords, or queries might be too large for the usual full-text search to provide the desired result. In such cases, the search either finds no intersections or returns a lot of irrelevant results. Qdrant is setting out to solve this problem with a neural network-based semantic search which can be used stand-alone or in conjunction with traditional search.
Qdrant utilizes applied AI and metric learning to provide users with an open-source neural search engine. This engine has proven popular with businesses looking to turn their unstructured data into an asset. The possible applications of this technology greatly vary, from product recommendations in e-commerce to image recognition and analysis of anomalies.
The trust and capital that leading investors have placed in Qdrant will allow it to develop and scale its technology further, with a focus on enterprise solutions and expanding its business team. This will be invaluable to the company as it continues to innovate and increase its consumer base.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Jan 2024
$30.1m
SERIES A
Apr 2023
$8.8m
SEED
Total funding: $41.2m
Company benefits
- Working in a passionate international team
- Flexible working hours
- Company events
- Choose any hardware
- Remote/home office possible
- Relocation and visa support (EU Blue Card)
- A collaborative and supportive work environment with opportunities for growth and advancement
- The chance to make a significant impact on an innovative technology with the potential to reshape industries
Company HQ
Prenzlauer Berg, Berlin, BE
Leadership
Andre Zayarni
(CEO & Co-Founder)Previously created JobBot-me, and served as CPO and CTO of MoBerries GmbH.
Andrey Vasnetsov
(CTO & Co-Founder)Previously worked as a Machine Learning Engineer as Tinkoff.ru, and was Lead Data Scientist at MoBerries.
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