AI/LLM Engineer (Go + Python)

AI/LLM Engineer for production LLM systems. Full remote, 10:00-19:00 MSK, 5/2. Salary $1500-2000 (paid every 2 weeks in USDT). Contact *****

Project: design and develop production system on LLM. Responsibilities: - Design and develop AI/LLM systems and AI agents - Build multi-step agentic workflows: routing, tool calling, state management - Work with Prompt Engineering and Context Engineering - Manage context, memory and dialogue state - Implement structured output and function/tool calling - Build RAG pipelines: chunking, embeddings, retrieval, reranking - Integrate LLM with APIs, databases and internal services - Develop backend services in Go and AI components in Python - Research new models and approaches, quickly test hypotheses - Select models considering quality, latency and cost - Build quality evaluation system: evals, regression tests, golden datasets, LLM-as-a-judge - Analyze logs and traces, improve quality and stability of agents - Implement retries, fallbacks, timeouts and error handling - Bring solutions from prototype to stable production

Go: production services; REST/gRPC API; concurrency; working with databases; microservice architecture. Python: AI services and backend; async; API; data processing; rapid prototyping. Also important: - Practical experience in developing production applications with LLM - Understanding of modern AI system architecture: prompt → context → tools → agent → state → evaluation - Experience with Prompt Engineering: system prompts, few-shot, prompt chaining, structured output - Experience with Context Engineering: memory, summarization, dynamic context assembly - Experience creating AI agents and agentic workflows - Working with LLM APIs and understanding different models - Understanding RAG: embeddings, vector search, retrieval, reranking, hybrid search - Understanding evals, regression testing and production log analysis - Experience with PostgreSQL, MongoDB, Redis, Docker, Git, CI/CD - Understanding production approaches: observability, scalability, latency, retries, fallbacks and cost control. Will be a plus: - Multi-agent systems - LangGraph - MCP - Langfuse / LangSmith - Elasticsearch / OpenSearch - Open-source LLM: Qwen, Llama, DeepSeek and others - vLLM / Ollama - Kafka / RabbitMQ - Kubernetes - Optimization of token usage, latency and cost of LLM - Guardrails and protection from prompt injection - Highload systems.

Fully remote. Schedule: 5/2 (Mon–Fri, 10:00–19:00 MSK). Trial period: 2 weeks of paid internship (full rate). Payment: 1500-2000 USD based on interview results, every 2 weeks in USDT. NDA agreement required.