Backend / AI Developer - Freelancer

We're building an AI Transformation platform for an enterprise client, focused on back-office process automation and AI-driven decision support. The platform integrates data from multiple business systems and implements AI agents to provide actionable insights and automated workflows.

• Approximately 2 years commercial experience in backend development with Python
• Hands-on experience with FastAPI or comparable modern web frameworks
• Good knowledge of PostgreSQL: schema design, query writing, optimization
• Experience building and consuming REST APIs
• Understanding of ETL and data synchronization concepts
• Working knowledge of Docker and Docker Compose
• Practical experience with LLMs and prompt writing; interest in agent-based systems
• Experience with agentic AI tools (e.g., Claude Code) and ability to critically verify their output
• Ability to write clear technical documentation
• Good communication skills and confidence working directly with client-side teams
• English language proficiency at B2+ / Upper-Intermediate level

Nice to have:

• Experience with agent frameworks (e.g., Agno, LangChain, LlamaIndex)
• Familiarity with MCP (Model Context Protocol)
• Basic skills in Next.js and React for front-end work
• Experience with observability and monitoring tools
• Experience integrating with CRM, analytics, or BI systems
• Background in enterprise or consulting projects

• Integrate data from multiple business sources (CRM, analytics, BI) into a cohesive data layer
• Build and deploy AI agents for business tasks like signal analysis, pricing, content/SEO, data classification and tagging
• Develop MCP (Model Context Protocol) servers for exposing domain-specific data
• Perform data engineering: schema design, ETL, synchronization, ensuring data quality
• Contribute to agent platform architecture including routing, cost control, access policies, telemetry for LLM calls
• Design and build backend APIs connecting data layer with agents and front-end applications
• Create user-facing tools driven by data and agent-generated insights
• Maintain infrastructure including containerization, database management, monitoring, and observability
• Document architectural decisions and maintain strict contracts between system layers