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Symphony Solutions
AI

Middle AI engineer (AI Agents)

Symphony Solutions · Дистанційно, UA

Actively hiring Posted 6 months ago

Responsibilities

  • Design and develop intelligent agents using Python and Autogen framework (or similar frameworks)
  • Collaborate with AI/ML teams to integrate LLMs (e.g., OpenAI, Anthropic, Google, etc.) into multi-agent workflows
  • Develop and maintain cloud-native applications and services (Azure / AWS / GCP)
  • Create robust APIs and integrate them with external/internal systems
  • Implement data ingestion, transformation, and storage logic using SQL, NoSQL, Columnar and Vector DBs
  • Support system scalability, performance, and maintainability using clean architecture principles
  • Contribute to agent orchestration logic, tool integrations, and interaction flows
  • Work closely with the Solutions Architect to align implementation with architecture vision
  • Write tests, maintain documentation, and participate in code reviews

Basic qualifications

  • 4+ years of experience in Python development, including async programming
  • Hands-on experience with LLM agent frameworks, especially Microsoft Autogen, Langchain, Crew AI, LlamaIndex, etc
  • Solid knowledge of cloud platforms: Azure, AWS, or GCP (at least one required)
  • Strong understanding of web development and modern API design (e.g., FastAPI, Flask)
  • Good experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Redis)
  • Understanding of Machine Learning basics (e.g., inference pipelines, embeddings, vector stores)
  • Familiarity with containerized development (Docker) and cloud deployment practices
  • Solid Git workflow experience, CI/CD pipelines knowledge
  • English proficiency (Intermediate or higher)

Preferred qualifications

  • Experience building multi-agent systems or working with agent orchestration tools
  • Exposure to RAG (Retrieval-Augmented Generation) and vector search (e.g., FAISS, Weaviate)
  • Familiarity with LangChain, LangGraph, LlamaIndex, CrewAI
  • Hands-on experience with streaming data, event-driven architecture, or message queues (e.g., Kafka, RabbitMQ and its cloud versions like Kinesis and MQ)
  • Knowledge of observability tools (e.g., Prometheus, Grafana, OpenTelemetry)
  • Experience with DevOps tools and infrastructure-as-code (Terraform, Helm, etc.)

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Ai Ai Engineer Data Engineer Robotics Generative Ai
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