Agentic AI engineer for enterprise systems

We are seeking a Senior Agentic AI Engineer with strong software engineering experience and expertise in designing, developing and deploying enterprise-grade AI solutions. The role focuses on building intelligent AI agents, multi-agent workflows and scalable AI-driven applications, integrating Large Language Models (LLMs) with enterprise systems and business processes. The ideal candidate will combine advanced AI engineering knowledge with practical experience delivering robust, production-ready solutions.

• Design, develop and implement Agentic AI applications and multi-agent systems.
• Build intelligent workflows using LLMs, agent orchestration frameworks and external tools.
• Develop scalable backend services and APIs to integrate AI capabilities with enterprise applications.
• Implement Retrieval-Augmented Generation (RAG), tool calling and context management.
• Optimise AI applications for performance, reliability, security and scalability.
• Deploy, monitor and maintain AI solutions in production environments.
• Collaborate with architects, engineering teams and business stakeholders on technical solutions.
• Contribute to technical architecture, development standards and engineering best practices.

• Strong hands-on software engineering experience, particularly with Python.
• Practical experience developing applications using Large Language Models.
• Knowledge of Agentic AI architectures, AI agents and multi-agent orchestration.
• Experience with frameworks such as LangGraph, LangChain, CrewAI, AutoGen or Semantic Kernel.
• Strong understanding of REST APIs, microservices and enterprise system integration.
• Experience with RAG, vector databases and LLM integration.
• Understanding of software development best practices, testing, CI/CD and production deployment.
• Ability to work independently in complex enterprise technology environments.
• Будет плюсом: Experience with Azure AI, Azure OpenAI, AWS Bedrock or Google Vertex AI; Knowledge of Docker, Kubernetes and cloud-native architectures; Experience with LLMOps, AI observability and model evaluation; Familiarity with security, governance and compliance considerations for enterprise AI; Previous experience within banking, financial services or large consulting environments

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