Generative AI Engineer

Role: Gen AI Developer

Location: Stockholm, Sweden

Work Mode: Hybrid Mode (2days on-site required per week)

Hiring Type: Freelance / B2B Contract

Duration: 6 to 12 months

Start Date: ASAP

Technical Competency Needed:

• Generative AI and Large Language Models (LLMs)
• Python and AI/ML application development
• Agentic AI and multi-agent architectures
• Model Context Protocol (MCP) – servers, tools, resources, and integrations
• LLM orchestration frameworks and agent workflows
• Prompt engineering and context management
• Tool/function calling and API integrations
• Retrieval-Augmented Generation (RAG)
• REST APIs, databases, SaaS platforms, and enterprise systems
• AI application architecture and scalable cloud services
• LLM evaluation, monitoring, logging, and observability
• Automated testing and AI/agent evaluation frameworks
• Security, performance, reliability, and cost optimization

Responsibilities:

• 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.