Full-stack Engineer

About the Role
We are looking for an experienced Senior Full-Stack Engineer to join our engineering team and build modern, scalable, AI-enabled digital products.
You will work across the full application stack, from backend services and APIs to modern web interfaces, cloud infrastructure, data integrations, and AI-powered features.
Key Responsibilities
Design, develop, and maintain scalable full-stack applications and enterprise platforms.
Build backend services and APIs using technologies such as Java / Spring Boot and Python / FastAPI.
Develop modern web applications using React, TypeScript, and Next.js.
Design and implement REST, GraphQL, webhook, and third-party API integrations.
Build and maintain distributed systems based on microservices and event-driven architectures.
Design reliable data models and optimize application and database performance.
Develop cloud-native applications and services running on public cloud platforms.
Work with relational, NoSQL, caching, and analytical databases.
Implement asynchronous processing, messaging, retry mechanisms, idempotency, and failure handling.
Build automated CI/CD pipelines and participate in deployment and infrastructure automation.
Improve application observability through logging, metrics, tracing, alerting, and operational dashboards.
Troubleshoot complex application, integration, and production issues across frontend, backend, and cloud environments.
Participate in architecture discussions, technical design, code reviews, and engineering best practices.
Take ownership of solutions from requirement analysis through development, testing, deployment, and production support.

AI & Intelligent Application Development
As AI becomes increasingly integrated into modern software products, this role also requires practical experience using AI technologies in application development.
You will:
Design and integrate LLM-powered features into production applications.
Integrate APIs from providers such as OpenAI, Anthropic Claude, Google Gemini, or equivalent platforms.
Build applications capable of working with multiple AI model providers.
Develop AI-enabled workflows for tasks such as content processing, translation, summarization, information extraction, classification, and automation.
Implement structured LLM outputs and integrate AI results into backend business logic.
Work with model routing, fallback strategies, usage monitoring, and AI API cost management.
Build internal engineering tools using AI-assisted development technologies.
Explore and implement MCP-based integrations, AI agents, tool calling, and AI-assisted workflows where appropriate.
Evaluate AI output quality, reliability, latency, and cost before introducing AI functionality into production systems.
Apply appropriate security, privacy, and data handling principles when integrating external AI services.

Required Qualifications
Several years of professional experience as a Full-Stack Engineer, Software Engineer, or similar role.
Strong backend development experience with Java and Spring Boot, Python, or comparable backend technologies.
Strong frontend development experience with React and TypeScript.
Experience designing and developing REST APIs and integrating third-party systems.
Solid understanding of microservices and distributed systems.
Experience with relational databases such as PostgreSQL, MySQL, or Oracle.
Experience with NoSQL or caching technologies such as MongoDB and Redis.
Experience working with Docker and cloud-based application deployment.
Experience with at least one major cloud platform, preferably GCP, AWS, or Azure.
Good understanding of software architecture, scalability, performance optimization, and system reliability.
Experience with CI/CD and modern software development workflows.
Strong troubleshooting and problem-solving capabilities.
Comfortable taking ownership across frontend, backend, integration, and deployment.
Professional working proficiency in English.

AI Requirements
Hands-on experience integrating LLMs or generative AI APIs into applications.
Experience using at least one major LLM platform such as OpenAI, Claude, Gemini, or equivalent.
Understanding of prompt design, structured outputs, tool/function calling, and AI API integration patterns.
Experience using AI coding tools such as Claude Code, Codex, GitHub Copilot, Cursor, or similar tools in professional software development.
Ability to identify where AI provides business value and where conventional software logic is more appropriate.
Understanding of key production AI considerations including:
model quality
hallucination and reliability
latency
token usage and cost
privacy and data security

Preferred Qualifications
Experience in one or several of the following areas is considered an advantage:
Python FastAPI.
React 18/19, Next.js, Vite, Tailwind CSS, or modern frontend frameworks.
GraphQL.
GCP technologies such as Cloud Run, Pub/Sub, Cloud SQL, BigQuery, and GCS.
Event-driven architectures and message-based processing.
Terraform or other Infrastructure as Code technologies.
Redis, MongoDB, BigQuery, or other modern data platforms.
E-commerce, IoT, telecom, or enterprise platform development.
High-volume or high-concurrency distributed systems.
AI model gateways or abstraction layers such as LiteLLM.
Model Context Protocol (MCP).
Retrieval-Augmented Generation (RAG).
AI Agents and tool-calling architectures.
AI observability, model evaluation, cost tracking, or multi-model routing.
Building internal developer tools or engineering automation using AI.

Personal Qualities
We believe you are:
Product-minded and capable of understanding both technical and business requirements.
Comfortable working across the entire software stack.
Curious about AI and emerging software technologies.
Pragmatic when deciding between AI-based solutions and traditional software engineering.
Proactive and comfortable taking ownership of complex technical problems.
Structured and analytical when troubleshooting distributed systems.
Able to work independently while collaborating effectively with developers, product owners, and other stakeholders.

Technology Environment
Depending on the project, the technology environment may include:
Java · Spring Boot · Python · FastAPI · React · TypeScript · Next.js · REST · GraphQL · PostgreSQL · MongoDB · Redis · BigQuery · Docker · GCP · AWS · Azure · Terraform · Pub/Sub · CI/CD · OpenAI · Claude · Gemini · LiteLLM · MCP · RAG · AI Agents
Location
Gothenburg
Employment
Full-time
Öppen för alla
Vi fokuserar på din kompetens, inte dina övriga förutsättningar. Vi är öppna för att anpassa rollen eller arbetsplatsen efter dina behov.