Senior AI Agentic Engineer

Main tasks

• Lead the design, development, and operation of production-grade Agentic AI and Generative AI solutions
• Provide hands-on software engineering and technical ownership of architecture, delivery quality, security, and engineering standards
• Translate business objectives into reliable, scalable, and secure AI-enabled services
• Guide engineering teams across the full service lifecycle, including requirements analysis, solution architecture, implementation, testing, deployment, observability, incident resolution, performance optimization, and continuous improvement
• Design and implement Generative AI and LLM-based solutions using prompt engineering, RAG, embeddings, semantic search, structured outputs, tool/function calling, evaluation, and performance optimization
• Develop Agentic AI services using frameworks such as LangChain/LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, OpenAI Agents SDK, Microsoft Agent Framework, or comparable technologies
• Define reliable, scalable, and secure agent architectures covering orchestration, tool integration, memory strategies, observability, error handling, guardrails, and lifecycle management
• Work with AI data and search technologies, including SQL/NoSQL databases, PostgreSQL, MongoDB, Azure AI Search, vector databases, embeddings, and semantic retrieval
• Guide engineering teams in CI/CD, automated testing, deployment automation, code reviews, GitHub/GitLab workflows, and Agile delivery practices
• Support cloud-native application development and deployment across AWS, Microsoft Azure, or GCP
• Define reusable patterns, technical guardrails, and engineering standards for AI services
• Mentor developers and review solution quality and architectural decisions
• Ensure AI solutions are scalable, secure, maintainable, and aligned with responsible AI principles
• Support security, data protection, model and agent risk management, and compliance considerations throughout the AI service lifecycle

Requirements

• Senior-level experience leading AI agent and service engineering initiatives, with hands-on development and technical ownership
• Strong programming skills in Python, Java, or Kotlin
• Strong knowledge of software design patterns, maintainable code structures, automated testing, and production-ready engineering practices
• Experience guiding engineering teams through CI/CD, automated testing, deployment automation, code reviews, and GitHub/GitLab workflows
• Experience with Agile delivery practices
• Experience with cloud-native application development and deployment on AWS, Microsoft Azure, or GCP
• Strong experience with APIs, integrations, scalable services, and operational readiness
• Hands-on experience designing and delivering Generative AI and LLM-based solutions
• Strong knowledge of prompt engineering, RAG, embeddings, semantic search, structured outputs, tool/function calling, evaluation, and performance optimization
• Practical experience building Agentic AI services using relevant agent frameworks
• Strong understanding of agent orchestration, tool integration, memory strategies, observability, error handling, guardrails, and lifecycle management
• Experience with AI data and search technologies, including SQL/NoSQL databases, PostgreSQL, MongoDB, Azure AI Search, vector databases, embeddings, and semantic retrieval
• Strong focus on Security and Responsible AI, including secure AI design, data protection, model and agent risk management, compliance, and responsible use of AI systems

Nice to have

• Experience with multiple Agentic AI frameworks, such as LangChain/LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, OpenAI Agents SDK, or Microsoft Agent Framework
• Experience across multiple cloud platforms, including AWS, Azure, and GCP

Other requirements

• Fluent in English
• Ability to simplify complex problems and obtain a workable solution;
• Customer focus and service delivery;
• Availability to work in EU.