Full Stack AI Engineer

Experience: 3–6 yearsDepartment: EngineeringReports To: Engineering Manager / Head of EngineeringAbout the RoleWe (Sweden Based Company) are looking for a skilled Full Stack Engineer to design, build, and maintain scalable web applications and AI-enabled platforms.You will work across the complete technology stack, including Next.js and React.js for frontend development, Python and FastAPI for backend services, and Docker and AWS ECS for application deployment.The ideal candidate should also have experience or strong interest in AI applications, large language models, AI agents, and Model Context Protocol (MCP) integrations.Key Responsibilities Develop responsive and high-performance frontend applications using Next.js, React.js and TypeScript. Build secure, scalable and well-documented backend APIs using Python and FastAPI. Design reusable frontend components and maintain clean application architecture. Integrate frontend applications with REST APIs, WebSockets and third-party services. Build AI-powered features using large language models, agents, tool calling and retrieval-augmented generation. Develop and integrate MCP servers and clients to connect AI agents with internal and external tools. Containerise applications and services using Docker. Deploy and operate applications on AWS using ECS, Fargate, ECR, Application Load Balancer, CloudWatch and related services. Design asynchronous workflows, background jobs and event-driven services. Implement authentication, authorisation and role-based access control. Write unit, integration and end-to-end tests. Monitor application performance, logs, errors and infrastructure health. Participate in architecture discussions, code reviews and sprint planning. Collaborate with product managers, designers, AI engineers and DevOps engineers. Troubleshoot production issues and continuously improve reliability, security and performance.Required Skills Strong experience with React.js, Next.js, JavaScript and TypeScript. Strong experience with Python and FastAPI. Good understanding of RESTful API design and backend service architecture. Experience with HTML, CSS and modern UI frameworks such as Tailwind CSS. Experience with relational databases such as PostgreSQL. Familiarity with SQLAlchemy, Alembic or similar ORM and migration tools. Experience containerising applications using Docker. Hands-on experience deploying applications on AWS ECS or ECS Fargate. Familiarity with AWS services such as ECR, IAM, S3, RDS, Secrets Manager, CloudWatch, Route 53 and Application Load Balancer. Understanding of CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins or similar tools. Good knowledge of Git, branching strategies and code review practices. Understanding of application security, authentication, authorisation and secure secret management. Strong debugging, problem-solving and communication skills.AI and MCP ExperienceCandidates should have practical experience or a strong understanding of: Large language model APIs such as OpenAI, Anthropic, Gemini or Amazon Bedrock. AI agents, tools, skills, memory and multi-step workflows. Model Context Protocol servers, clients, tools and resources. Prompt engineering and structured LLM outputs. Retrieval-augmented generation and vector databases. AI guardrails, access controls and responsible tool execution. Frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel or similar technologies. Evaluating AI responses for quality, accuracy, latency and cost.Preferred Qualifications Experience building multi-agent or skills-based AI applications. Experience with asynchronous Python, Celery, Temporal, SQS or event-driven systems. Familiarity with infrastructure as code using Terraform or AWS CDK. Experience with Redis, Elasticsearch, OpenSearch or vector databases. Familiarity with WebSockets and real-time application development. Experience with Playwright, Cypress, Pytest or Jest. Understanding of microservices, distributed systems and observability. Experience working in startup or high-growth product environments. Familiarity with Kubernetes is beneficial but not mandatory.What We Expect Ownership of features from design through deployment and production support. Ability to write clean, maintainable and testable code. A security-first and reliability-focused engineering mindset. Ability to work independently while collaborating effectively with the wider team. Curiosity about emerging AI technologies and willingness to learn quickly. Clear communication regarding progress, blockers, risks and technical decisions.What We Offer Opportunity to build production-grade AI and agentic applications. Exposure to modern cloud, AI and full-stack engineering technologies. Ownership of technically challenging and high-impact projects. Collaborative and innovation-focused work environment. Competitive compensation based on skills and experience. Flexible working arrangements based on company policy.