Summary
✨ AI‑Generated
Join an experienced engineering team building production-grade Generative AI applications. You will own major parts of the frontend experience, transforming LLM, retrieval, tool-calling and agentic capabilities into intuitive, responsive and trustworthy interfaces while collaborating with backend engineers, designers and data specialists.
Highlights
Build production-grade GenAI applications in a large-scale regulated environment, with significant ownership of user-facing experiences and close collaboration across engineering, design, and data teams.
Description
Senior Front-End Developer – GenAI / Agentic AI
Location: Vilnius, Lithuania
Working model: Hybrid
Salary: Up to €7,400 gross per month
We’re looking for an experienced Senior Front-End Developer to join a team building production-grade Generative AI products within a large-scale, regulated environment.
This is not a traditional front-end role with an AI feature added on.
You’ll be building the user-facing experiences around LLMs and increasingly sophisticated AI agents, helping create products that are intuitive, responsive and trustworthy.
You’ll work within a multidisciplinary squad alongside backend engineers, designers and data scientists, taking capabilities such as RAG, tool calling and agentic workflows and turning them into polished production applications.
What you’ll be working on
You’ll take significant ownership of the front-end experience for GenAI applications, designing and developing modern interfaces around AI-powered functionality.
A major focus will be creating effective user experiences for agentic workflows.
This includes giving users visibility into what an agent is doing, implementing approval and human-review steps, communicating progress and failures clearly, and ensuring users remain in control when AI systems take meaningful actions.
Your responsibilities will include:
Designing and building responsive, accessible front-end applications for AI-powered productsDeveloping conversational interfaces and experiences around AI agentsBuilding UX patterns for streaming LLM responsesIntegrating RAG, tool calling and agentic workflows into user-facing productsImplementing source citations and transparency around AI-generated responsesCreating human-in-the-loop controls and approval workflowsDesigning clear experiences around agent progress, uncertainty and failure statesIntegrating front-end applications with backend APIs, tools and ML systemsWorking closely with design, backend and data science teamsWriting high-quality production code and reviewing pull requestsContributing to secure, compliant and accessible AI applicationsHelping monitor AI workflows including latency, token usage, tool failures and user outcomes
What we’re looking for
The key requirement for this position is hands-on experience working with agentic workflows.
We’re particularly interested in engineers who have already encountered the challenges of building interfaces around AI agents rather than simply integrating a basic chatbot or LLM API.
You should bring:
Strong commercial front-end development experienceReact, Angular, Vue or a similar modern front-end frameworkStrong TypeScript and modern web application development experienceProduction experience building GenAI applicationsHands-on experience with agentic workflowsExperience with LLM tool/function callingExperience with RAGExperience building chat or conversational AI interfacesExperience with AI evaluation, tracing, feedback loops or error analysisUnderstanding of observability for GenAI/agentic systemsStrong product thinking and an ability to simplify complex AI functionality
An understanding of GenAI security is also valuable, particularly around areas such as prompt injection, sensitive information exposure, authorisation, rate limiting and controlling the cost and behaviour of AI workflows.
Why this role?
You’ll be working on GenAI products where AI is a fundamental part of the product experience rather than an experimental side project.
The engineering challenges go well beyond rendering model responses.
You’ll help determine how users interact with autonomous workflows, understand what an agent is doing, approve important actions, recover from failures and confidently use non-deterministic AI systems in a production environment.