AI Engineer (Agentic Systems)

Andersen is hiring an AI Engineer (Agentic Systems) for a project developing AI-powered assistants and intelligent agents for a global fintech and digital trading platform. The customer is an international technology company operating a digital platform that brings together a range of financial and investment-related services. Its offering includes access to various market instruments, analytical and educational tools, and functionality designed to support different types of users and investment approaches. The company serves customers across multiple markets through a digital-first model and continues to expand its platform with additional features, services, and partnership opportunities. The project is focused on developing and integrating AI-powered capabilities into a global fintech and digital trading platform. It includes building a client-facing AI assistant, AI-generated trading strategies, and intelligent agents for business process automation, while supporting the modernization and internalization of the technology ecosystem.

Responsibilities: - Designing, building and running LLM agents in production, both client-facing and internal. - Building MCP servers on top of existing databases and production systems and orchestrating several internal and external MCP servers under one agent. - Designing memory, context management and RAG for production use. - Setting up evaluation, handling edge cases and improving agents step by step after release. - Working in an architecture that combines databases, interfaces, agents and orchestrator applications. - Working on Amazon Bedrock and/or Microsoft Foundry.

Requirements: - Experience in the IT field as a Software Engineer, ML Engineer, AI Engineer for 3+ years. - Hands-on production experience with Amazon Bedrock and/or Microsoft Foundry (Azure AI Foundry, Azure OpenAI). - Built and shipped LLM agents to production, both client-facing (customer assistants, conversational AI) and internal workflow automation agents. - Strong experience with at least one agent framework: LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, Strands Agents or OpenAI Agents SDK. - Deep MCP experience: building MCP servers on top of existing databases and systems, integrating external MCP servers and orchestrating several of them under one agent. - Production-grade RAG, memory and context engineering: embeddings, chunking, hybrid search, reranking, vector databases, short- and long-term agent memory. - Experience with LLM evaluation, guardrails and monitoring of agents in production, and iterative improvement based on real usage and failure cases. - Understanding of system architecture combining databases, APIs, agents and orchestrator applications, plus practical Docker and CI/CD experience. - Level of English – from Upper-Intermediate and above.

Nice to have: - Trading, investing, brokerage or crypto domain knowledge combined with AI engineering. - Fintech or regulated industry background (compliance, data protection, auditability of AI outputs). - Broader AWS or Azure cloud experience around the Bedrock/Foundry stack. - Experience with LLM evaluation and observability tools (e.g. LangSmith, Langfuse, Ragas, custom eval pipelines). - Deep practical mastery of agentic development tools used to deliver full prototypes quickly.

Compensation: 2300–3600 EUR per month.