AI Developer

Job Title: AI DeveloperLocation: Stockholm, Sweden Hybrid 2days office per weekJob type: Contract Required Technical Skill Set**AI-powered applications and agentic workflows, Model Context Protocol (MCP) servers, RAG (Retrieval-Augmented Generation) solutions Technical Competency Needed: Generative AI and Large Language Models (LLMs)Python and AI/ML application developmentAgentic AI and multi-agent architecturesModel Context Protocol (MCP) – servers, tools, resources, and integrationsLLM orchestration frameworks and agent workflowsPrompt engineering and context managementTool/function calling and API integrationsRetrieval-Augmented Generation (RAG)REST APIs, databases, SaaS platforms, and enterprise systemsAI application architecture and scalable cloud servicesLLM evaluation, monitoring, logging, and observabilityAutomated testing and AI/agent evaluation frameworksSecurity, performance, reliability, and cost optimizationEligibility Criteria: This Eligibility Criteria applicable if matching profile found in Sweden - Security clearance eligible for national security & autonomy requirements - Swedish residency of continuous 3+ years / SE citizenshipResponsibilities: • Design, develop, and integrate AI-powered applications and agentic workflows using modern LLM technologies.• Build and maintain Model Context Protocol (MCP) servers, tools, resources, and integrations to enable AI agents to interact with enterprise systems.• Develop orchestration frameworks and multi-agent workflows for coordinating AI agents, tools, APIs, and business processes.• Integrate LLMs with REST APIs, databases, SaaS platforms, internal services, and external tools through secure and scalable architectures.• Implement prompt engineering, tool/function calling, context management, memory, and RAG (Retrieval-Augmented Generation) solutions.• Develop production-grade AI services with strong focus on scalability, reliability, observability, security, and performance.• Work with engineering and product teams to translate business requirements into AI/agent-based solutions and technical architectures.• Evaluate and optimize LLM models, agent performance, prompts, workflows, latency, and operational costs.• Build automated testing, monitoring, logging, and evaluation frameworks to ensure quality and reliability of AI agents and MCP integrations.• Stay current with emerging GenAI, MCP, agent orchestration, LLM, and AI engineering technologies, and contribute to best practices and technical standards.