Global AI Application Engineer
About the Role
We are hiring an AI Application Engineer to join a growing AI team within a global retail organization, developing advanced GenAI and Agentic AI solutions for real business use cases for Global Business Units.
This is a hands-on engineering role with strong technical ownership. You will work across the full AI application lifecycle, from understanding business requirements and designing the solution through implementation, integration, evaluation, production deployment, monitoring, and continuous improvement.
What You’ll Do
Design and build production-grade GenAI and Agentic AI applications
Develop multi-step agent workflows involving tool calling, state management, routing, retries, checkpoints, and human-in-the-loop
Build agent orchestration using LangGraph, LangChain, or similar frameworks
Design and optimize RAG, vector search, retrieval, reranking, and context-management solutions
Integrate AI applications with enterprise APIs, databases, search services, and frontend applications
Build scalable backend services using Python and FastAPI
Evaluate AI outputs for accuracy, relevance, hallucination, latency, and cost
Implement testing, tracing, monitoring, and observability for production AI applications
Improve system reliability, scalability, security, and performance
Work closely with Product, Data Science, Engineering, and Business teams
What We’re Looking For
Proven experience building and deploying AI applications into production
Strong Python and software engineering fundamentals
Hands-on experience with LLMs, RAG, Agentic AI, and tool/function calling
Experience with LangGraph, LangChain, or equivalent orchestration frameworks
Experience building APIs and integrating AI applications with enterprise systems
Able to work proactively and independently with strong end-to-end ownership
Strong communication skills and ability to explain technical decisions and trade-offs clearly
Relevant Technologies
Python, FastAPI, LangGraph, LangChain, Azure OpenAI/OpenAI, RAG, Vector Search, PostgreSQL, Databricks, Docker, CI/CD, Langfuse, LangSmith, Grafana
Equivalent technologies are welcome. The focus is on strong engineering fundamentals and real AI production experience.