Our team is at the forefront of GenAI-powered solutions developing cutting-edge services to enhance user experiences, optimize internal processes, and explore new business opportunities. You’ll work on scalable, high-impact AI projects, collaborate with cross-functional teams, and contribute to proofs-of-concept, and production-ready AI applications.

Main responsibilities:

• Design, develop, and maintain backend services for Product Solutions Platform.

• Build high-performance, scalable, and distributed systems.

• Work with Java, Spring, Kafka, OpenSearch to enhance our product, ensuring safety, efficiency, and responsiveness.

• Develop internal tools for monitoring, debugging, and optimizing applications at scale.

• Ensure observability, reliability, and fault tolerance across all services.

• Collaborate with cross-functional teams including Software Engineers, UX Designers and Product Managers.

• Maintain a strong focus on code quality, security, and best practices in software development.

• Build AI/ML-enabled products.

• This is a remote role.
  

REQUIREMENTS

• Bachelor’s degree in Computer Science , Information Technology, or related fields.

• Advanced spoken and written English.

• Production-level experience in backend development using Java, Go, Python or any other modern language.

• Deep understanding of distributed systems and experience building high-scale microservices and event-driven architectures.

• Experience with observability, logging, and monitoring tools for debugging and performance analysis.

• Experience with cloud platforms (AWS) and containerized deployments (Docker, Kubernetes).

• A problem-solving mindset with the ability to debug distributed systems.

• Strong communication skills and the ability to work effectively in a collaborative environment.
  

Nice to Have:

• Production experience integrating LLM APIs (OpenAI, Anthropic, Gemini, etc.) into scalable, real-world systems.

• Practical experience with LangChain , LlamaIndex , or similar LLM orchestration frameworks.

• Experience with developing AI Agents, the world of tools and how AI agents can leverage external functionalities and APIs.

• Familiarity with context and memory management — including session handling, conversation history strategies, long-context optimization, and state-of-the-art agent design.

• Experience with RAG, Prompt Engineering, response validation, Vector Data Bases and AI guardrails.