ai engineer for LLM-powered services

Grid Dynamics provides technology consulting, platform and product engineering, AI, and advanced analytics services. The company helps enterprise organizations address technical challenges and achieve business outcomes during business transformation.

• Design, build, and deploy production-grade LLM-powered services, microservices, and APIs using Python and TypeScript;
• Implement advanced meta-prompting frameworks and prompt optimization techniques for deterministic, context-aware AI outputs;
• Develop scalable Retrieval-Augmented Generation (RAG) pipelines and integrate vector databases for context engineering and semantic code search;
• Orchestrate LLM workflows using LangChain or LlamaIndex to connect multi-agent tools, system constraints, and domain knowledge bases;
• Implement automated testing, LLM evaluation, and quality assurance frameworks to benchmark model performance, accuracy, and output consistency;
• Build containerized microservices and automated CI/CD pipelines using Docker for deployment and sandboxed execution;
• Act as a hands-on Senior Developer and Mentor by guiding mid-level engineers, establishing coding standards, and conducting code reviews.

• 5+ Years of commercial software development experience with production-grade code in Python and TypeScript;
• Strong hands-on experience integrating major LLM APIs, including OpenAI and Anthropic Claude, into production software;
• Deep expertise in meta-prompting, advanced prompt engineering, and context window optimization;
• Practical experience building and deploying RAG systems using vector databases such as Pinecone, Weaviate, or ChromaDB;
• Solid hands-on experience with LLM orchestration frameworks such as LangChain or LlamaIndex and embedding models;
• Demonstrated experience developing automated testing, evaluation, and observability pipelines for AI/LLM applications;
• Strong proficiency in Docker containerization, API design, and CI/CD automation pipelines;
• Experience as a Senior/Lead Developer or Technical Mentor in a fast-paced R&D environment;
• Excellent problem-solving skills and software engineering discipline;
• Excellent written and verbal English communication capabilities;
• Nice to have: experience with multi-agent architecture, agent orchestration, and progressive disclosure patterns; practical knowledge of Model Context Protocol (MCP) or emerging context-sharing standards; hands-on experience with LLM-as-a-Judge evaluation methodologies and A/B testing frameworks; experience building developer tools, CLI utilities, or SDKs; familiarity with OAuth/OIDC security and enterprise authentication protocols.

• Competitive salary;
• Flexible schedule;
• Benefits package including medical insurance and sports benefits;
• Corporate social events;
• Professional development opportunities;
• Well-equipped office.