AI Engineer – Golang

Sourced from tealhq.com

Design and build production-grade agentic AI applications and scalable backend services using Python and Golang. The role centers on LLM integration, multi-agent orchestration, RAG, and enterprise system integrations deployed on Kubernetes and cloud platforms. Collaborate with architects and product teams to deliver secure, reliable, production-ready AI solutions.

• Design, develop, and maintain production-grade AI applications using Python and Golang
• Build agentic AI workflows with LangGraph, LangChain, or similar frameworks
• Integrate LLMs from OpenAI, Google Gemini, Anthropic, and other enterprise platforms
• Develop multi-agent systems with planning, reasoning, tool execution, and context management
• Implement MCP integrations and connect agents to APIs, databases, and external tools
• Develop RESTful APIs, microservices, and backend components
• Implement RAG, embeddings, vector search, and knowledge retrieval
• Containerize and deploy applications using Docker, Kubernetes, and cloud platforms
• Implement automated testing, AI evaluation, monitoring, tracing, and performance optimization
• Ensure security, reliability, scalability, and data privacy of AI applications

• At least 5 years of professional software development experience
• Strong hands-on Python development experience
• Experience with Golang for backend development, APIs, or distributed services
• Practical experience building Agentic AI or Generative AI applications with LLMs
• Experience with LangGraph, LangChain, LlamaIndex, or comparable orchestration frameworks
• Strong understanding of REST APIs, microservices, asynchronous programming, and distributed systems
• Experience with prompt engineering, LLM integration, tool calling, and structured outputs
• Knowledge of RAG, embeddings, vector databases, and semantic search
• Experience with Git, CI/CD, automated testing, Docker, and Kubernetes
• Bachelor's or master's degree in Computer Science or related field, or equivalent experience

• Experience implementing MCP servers, clients, or agent-to-tool integrations
• Experience with multi-agent orchestration frameworks such as LangGraph
• Familiarity with Pinecone, Milvus, Weaviate, or FAISS
• Experience with PostgreSQL, Redis, or Kafka
• Experience deploying AI applications on AWS, Azure, or GCP
• Knowledge of AI evaluation frameworks, observability, guardrails, and production tracing
• Experience with network automation, cybersecurity, enterprise infrastructure, or Cisco technologies