Senior Agentic AI Engineer

This is a fully remote position, open to applicants in Poland.

📋 Description

• Create, develop, and implement Agentic AI solutions utilizing platforms like Azure OpenAI Services, Google Vertex AI, Amazon Bedrock, or comparable technologies.

• Construct and manage AI agents and multi-agent workflows, utilizing contemporary agentic frameworks such as LangChain, LangGraph, and Semantic Kernel.

• Design intelligent applications that integrate LLMs, retrieval systems, tool execution, and memory functionality.

• Establish robust RAG pipelines, knowledge grounding, and enterprise search integrations.

• Develop production-quality agent evaluation, monitoring systems, guardrails, and safety protocols.

• Collaborate within cross-functional agile teams to deliver comprehensive AI systems, from initial exploration and feature engineering to training, validation, deployment, and ongoing enhancement.

• Analyze large, high-dimensional datasets employing AI/ML techniques to derive value and produce actionable insights.

• Act as a technical advisor during client interactions, identifying potential opportunities, suggesting solutions, and sharing best practices regarding GenAI and agentic architecture.

⛳️ Requirements

• Master’s degree in Artificial Intelligence, Data Science, Computer Science, Engineering, Mathematics, or a related discipline.

• Several years of practical experience in applied machine learning or AI engineering roles.

• Strong proficiency in Python programming language.

• Extensive experience with AI platforms such as Azure OpenAI, Google Vertex AI, Amazon Bedrock, or similar alternatives.

• Hands-on knowledge of developing AI agents, encompassing tool usage, reasoning workflows, planning loops, and autonomous task execution.

• Understanding of agentic frameworks and orchestration tools like LangChain, LangGraph, Semantic Kernel, or similar.

• Experience in implementing RAG pipelines, knowledge grounding, and enterprise integrations for agent-based applications.

• Familiarity with deploying AI systems in production, including MLOps/LLMOps practices, evaluation strategies for LLMs and agents, and cloud ML ecosystems (Azure, AWS, GCP).

• Experience with Databricks.

• Proven capability to effectively manage complex, high-volume, multi-source data.

• Strong communication skills and a business-oriented mindset, with the ability to convert technical AI outputs into strategic value for clients and stakeholders.

• Proficiency in both spoken and written English.

• Preferred: experience with ML/data libraries such as scikit-learn, pandas, PyTorch, or TensorFlow, along with insights into deep learning and classical ML techniques.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Flexible working hours and remote work options.

• Continuous learning and professional development opportunities.

• Health and wellness benefits, including medical, dental, and vision coverage.

• Collaborative and innovative work environment.