Senior AI Engineer

Quick Facts

• Build conversational AI agents across chat, voice, email, and APIs
• Cloud-based development with evaluation and monitoring for continuous improvement

Description

Design, build, and maintain scalable conversational AI systems operating across multiple channels in cloud environments. Implement orchestration and decision logic in Python, connect AI to corporate systems and external models, and optimize prompts and models using approaches such as fine-tuning and RAG. Establish evaluation and monitoring pipelines with dashboards, metrics, and human-in-the-loop feedback to maintain model quality and trust.

Responsibilities

• Develop and launch conversational AI systems across chat, voice, email, and APIs
• Architect microservices and asynchronous systems for AI applications with high availability and performance
• Use Python to implement orchestration and decision logic (control layer for tools, workflows, and system interactions)
• Optimize AI models via fine-tuning and LoRA; make data-driven decisions between FT vs RAG
• Create prompt engineering libraries and define evaluation protocols for prompt performance
• Implement monitoring and evaluation frameworks with metrics and human-in-the-loop feedback
• Work with data specialists to design pipelines for collecting, cleaning, and structuring data for AI agents
• Build CI/CD pipelines, container standards, and cloud strategies for migrations, cost optimization, and high availability

Requirements

• Strong Python background for AI model integration, automation, and orchestration logic
• 1–2 years of hands-on experience with Generative AI and LLMs
• Practical machine learning engineering experience: data preparation, vector databases in the cloud, and training/optimizing models
• Backend and frontend architecture experience
• Deep understanding of ML evaluation, tuning, and prompt engineering
• Experience with AWS, GCP, or Azure, including containers and CI/CD pipelines
• Experience with agentic frameworks (LangChain, LangGraph) and multi-agent system design
• Comfort with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn (plus)

Benefits

• Stable income (Employment Contract or B2B) and Employee Stock Purchase Plan participation
• Benefits package: health insurance, multisport, shopping vouchers
• Flexible schedule with opportunity to work remotely within Poland
• Option to work abroad up to 60 days annually; business-driven relocation opportunities
• Growth opportunities: career roadmap, leadership development, career advising, soft skills, and well-being programs
• Certifications (GCP, Azure, AWS) and unlimited access to learning platforms
• English classes
• Corporate social events and well-being events; referral bonuses