AI Agent Engineer

We are Randstad, a global leader in talent solutions. We are looking for a professional to join our Agentic PMSO team, working on an AXIA / Data CoE project.

The professional will be responsible for designing, developing, and operating AI Agents (Agentic AI) focused on corporate process automation, data analysis, and integration with enterprise systems (ERP, APIs, and internal platforms). Responsibilities include building multi-agent flows, orchestrating complex tasks, and implementing reasoning, memory, and decision-making capabilities.

Seniority: Senior. The professional must have the autonomy to design, implement, and operate AI Agents in production.

Hard Skills:

• Agentic AI & GenAI: Development of agents using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, Agno, or equivalents
• Agent patterns: Tool use, MCP/A2A/ACP protocols, RAG, short-term and long-term memory, multi-agent orchestration
• Advanced prompt engineering, response evaluation, and hallucination control
• Microsoft Stack: Azure OpenAI, Azure AI Foundry, Copilot Studio, Power Platform, Azure DevOps, Azure Functions, Logic Apps, Microsoft Graph API, Entra ID
• Google Cloud Stack: Gemini Enterprise, Vertex AI, BigQuery, Cloud Run, Cloud Functions, Cloud Storage, Model Armor, Apigee
• Advanced Python, REST APIs, FastAPI/Flask, event-driven architecture, and microservices
• Data & RAG: Ingestion pipelines, chunking, indexing, vector databases (Pinecone, FAISS, Vertex Matching Engine, Azure AI Search)
• Observability, quality, and governance: Logging, tracing, metrics, prompt testing, version control with Git

Desirable Hard Skills:

• AgentOps / LLMOps
• Governance: OWASP for LLM, Responsible AI
• Multi-cloud architecture (Azure + GCP)
• Observability: Datadog, Application Insights, Google Model Armor
• Intelligent Automation (RPA + AI)

Expected Soft Skills:

• Translate business requirements into viable AI Agent solutions
• Communication with technical and non-technical stakeholders
• Documentation of architecture, decision flows, and integrations
• Proactivity in identifying risks (security, cost, response quality)
• Product mindset: Reusability, scalability, governance, and compliance