We are seeking a talented and driven GenAI/AI Backend Engineer to join our team. In this role, you'll be responsible for designing versatile, scalable backend solutions, integrating cutting-edge AI technologies, and ensuring seamless deployment and performance of AI-powered applications. Partnering closely with Data Science, DevOps, and cloud teams, you’ll play a pivotal role in bringing advanced AI workflows and robust solutions to life.
Responsibilities
- Develop and optimize backend services for AI and LLM applications
- Integrate, scale, and manage LLM-based applications in cloud environments
- Implement and manage CI/CD pipelines for streamlined deployment
- Monitor and continuously optimize the performance of AI services
- Ensure effective observability and logging for tracking LLM API performance
- Collaborate with DevOps and Data Science teams to improve workflow efficiency and system reliability
- Design and maintain backend architecture for scalable, LLM-powered APIs
- Facilitate deployment and scaling of AI solutions in cloud platforms, with a preference for Azure
- Build APIs and microservices to support AI-driven functionalities
Requirements
- 2+ years of experience in AI Engineering, specializing in backend development
- Strong proficiency in Python backend engineering, especially with FastAPI
- Expertise in integrating LLM APIs (e.g., OpenAI) into production workflows
- Proficiency in prompt engineering, agentic workflows, and orchestration approaches
- Capability to address LLM operational challenges such as latency, cost control, retries, and fallback mechanisms
- Knowledge of backend architecture for scalable LLM integrated APIs with high-performance requirements
- Working knowledge of databases, including SQL/NoSQL, Redis, and streaming platforms such as Kafka
- Familiarity with platforms such as Databricks and MCP for enhanced AI workflow management
- Strong communication skills in English (minimum B2+ level proficiency)
- Flexibility to work in shifted working hours up to 10 pm Kyiv time
Nice to have
- Showcase of hands-on experience in building and optimizing agentic workflows
- Deep understanding of Model Context Protocol (MCP) and its applications in AI systems