AI/ML Engineer

What You'll Do

• We are seeking an AI/ML Engineer to support the design, development, and deployment of enterprise AI, Generative AI, and agentic AI solutions. This role will work within cross-functional delivery teams to build scalable AI capabilities that integrate with business processes, enterprise applications, and data platforms.
• The ideal candidate will have strong hands-on experience with Python, LLMs, RAG, prompt engineering, agentic workflows, model evaluation, and production AI engineering. Senior candidates should bring deeper technical leadership, architecture, and delivery experience.

Must-Have

• Czech location

Responsibilities

• Design, build, and deploy production AI/ML and Generative AI solutions
• Develop LLM-powered applications, RAG pipelines, and agentic AI workflows
• Build multi-agent and multi-step workflows using LangChain, LangGraph, or similar frameworks
• Integrate LLMs with enterprise systems, APIs, tools, and data sources
• Develop retrieval, prompt engineering, context management, and tool/function-calling capabilities
• Build evaluation frameworks to measure model and agent accuracy, quality, and reliability
• Implement AI guardrails, validation, monitoring, and human-in-the-loop controls
• Develop scalable Python-based AI services and integrations
• Support production deployment, monitoring, and continuous improvement of AI solutions
• Partner with engineering, data, product, and business teams to translate requirements into working solutions

Qualifications

• Strong hands-on Python development experience
• Experience building and deploying AI/ML and Generative AI applications
• Hands-on experience with LLMs, RAG, and agentic AI
• Experience with LangChain, LangGraph, or similar frameworks
• Experience with AI agents, tool/function calling, and multi-step workflows
• Strong understanding of prompt engineering and context management
• Experience with model/LLM evaluation and production monitoring
• Knowledge of AI guardrails, reliability, and responsible AI practices
• Experience with MLOps/LLMOps and production AI deployments
• Experience with APIs and enterprise integrations
• Experience with vector databases and semantic search preferred
• Experience with AWS, Azure, or GCP preferred

Preferred Qualifications

• Experience building AI solutions in pharmaceutical, biotechnology, healthcare, or another regulated industry.
• Experience supporting GxP or other regulated use cases.
• Familiarity with Responsible AI, AI governance, security, and privacy requirements.
• Experience with vector databases and semantic search.
• Experience with CI/CD and cloud-native application development.
• Experience working within Agile or product-based delivery teams.