Our Customer:
A product-oriented technology company building AI-powered automation solutions for real-time operational processes and intelligent decision-making systems.
Your tasks:
Develop and maintain AI agent workflows for automated data analysis and operational actions.
Build LLM-based solutions including RAG pipelines, tool integrations, and structured response generation.
Create monitoring, evaluation, and validation processes for AI systems in production.
Integrate AI services with backend systems, APIs, and streaming data pipelines.
Collaborate with Product and Engineering teams to implement business logic into AI-driven solutions.
Improve reliability, scalability, and performance of AI and ML components.
Participate in deployment, testing, and optimization of production AI applications.
Required experience and skills:
3+ years of experience in Data Science, Machine Learning, or AI Engineering.
Solid understanding of Machine Learning fundamentals and model evaluation approaches.
Strong practical experience with GenAI and LLM-based applications in production environments.
Hands-on experience building AI agents, multi-step workflows, or orchestration pipelines.
Experience with prompt evaluation, monitoring, testing, and observability of AI systems.
Strong Python programming skills.
Experience working with modern LLM platforms and APIs such as OpenAI, Anthropic, Google, or Microsoft.
Experience integrating AI solutions with external tools, APIs, or backend services.
Ability to work independently and take ownership of technical solutions.
English level — Upper-Intermediate (B2) or higher.
Would be a plus:
Experience with cloud platforms, especially Microsoft Azure AI services.
Knowledge of vector databases and retrieval systems.
Experience with real-time or streaming data platforms.
Background in logistics, IoT, or operational analytics domains.
Familiarity with MLOps and CI/CD practices for AI systems.
