Senior Agentic AI Engineer

Quick Facts

• Role: Senior Agentic AI Engineer

• Focus: Agentic AI systems, LLM-powered autonomous agents, and production-grade AI pipelines

Description

Design, develop, and deploy agentic AI solutions and multi-agent workflows that combine LLMs, retrieval, tool execution, and memory for autonomous task completion. Build robust RAG pipelines and enterprise search integrations, then implement evaluation, monitoring, guardrails, and safety mechanisms for reliable production behavior.

Responsibilities

• Design, develop, and deploy Agentic AI solutions using platforms such as Azure OpenAI Services, Google Vertex AI, Amazon Bedrock, or similar
• Build and orchestrate AI agents and multi-agent workflows using agentic frameworks (e.g., LangChain, LangGraph, Semantic Kernel)
• Develop intelligent applications combining LLMs, retrieval, tool execution, and memory
• Implement RAG pipelines, knowledge grounding, and enterprise search integrations
• Engineer production-grade agent evaluation, monitoring, guardrails, and safety mechanisms
• Work in cross-functional agile teams to deliver end-to-end AI systems (exploration, feature engineering, training, validation, deployment, and continuous improvement)
• Investigate and analyze large, high-dimensional datasets to generate actionable insights
• Serve as a technical advisor during client engagements by recommending GenAI/agentic architecture solutions and best practices

Requirements

• MSc in Artificial Intelligence, Data Science, Computer Science, Engineering, Mathematics, or a related field
• A few years of hands-on experience in applied machine learning or AI engineering
• Solid proficiency in Python
• Strong experience with AI platforms such as Azure OpenAI, Google Vertex AI, Amazon Bedrock, or similar
• Practical knowledge building AI agents (tool-use, reasoning workflows, planning loops, autonomous execution)
• Familiarity with agentic frameworks and orchestration tools (e.g., LangChain, LangGraph, Semantic Kernel)
• Experience implementing RAG pipelines, knowledge grounding, and enterprise integrations
• Experience deploying AI systems into production, including MLOps/LLMOps and LLM/agent evaluation strategies
• Ability to handle complex, high-volume, multi-source data
• Strong communication skills and business orientation; proficiency in spoken and written English and Polish at least B2

Benefits

Not specified in the provided posting.