Job description:
AI Engineer – Agentic AI & LLM Applications (Azure)
Role Summary
AI Engineers will build, evaluate, and operate LLM-powered agents and workflows using Microsoft AI Foundry and Azure AI services. This role combines deep Python development with prompt engineering, agent orchestration, and AI evaluation to deliver reliable supply chain AI solutions.
Key Responsibilities
- Develop AI agents for supply chain planning, forecasting, exception handling, and decision support.
- Implement agent orchestration logic (task routing, tool invocation, memory management).
- Build RAG pipelines using Azure AI Search, vector embeddings, and enterprise data sources.
- Design and optimize prompts and system instructions for accuracy and consistency.
- Implement automated evaluation pipelines:
- Prompt and response evaluation
- Regression testing for agent behavior
- Cost and latency monitoring
- Apply guardrails and safety mechanisms (policy enforcement, output validation).
- Integrate AI services into APIs and applications.
- Collaborate with data engineers to ensure data quality and relevance.
Required Skills & Experience
- Strong Python engineering skills.
- Hands-on experience with LLMs and agent frameworks.
- Solid understanding of prompt engineering, embeddings, vector search.
- Experience deploying AI solutions on Azure.
- Experience with AI evaluation, testing, and monitoring.
Nice to Have
- Full-stack development experience.
- Familiarity with Responsible AI practices.
- Supply chain AI or analytics experience.
Profile description:
AI Engineer – Agentic AI & LLM Applications (Azure)
Role Summary
AI Engineers will build, evaluate, and operate LLM-powered agents and workflows using Microsoft AI Foundry and Azure AI services. This role combines deep Python development with prompt engineering, agent orchestration, and AI evaluation to deliver reliable supply chain AI solutions.
Key Responsibilities
- Develop AI agents for supply chain planning, forecasting, exception handling, and decision support.
- Implement agent orchestration logic (task routing, tool invocation, memory management).
- Build RAG pipelines using Azure AI Search, vector embeddings, and enterprise data sources.
- Design and optimize prompts and system instructions for accuracy and consistency.
- Implement automated evaluation pipelines:
- Prompt and response evaluation
- Regression testing for agent behavior
- Cost and latency monitoring
- Apply guardrails and safety mechanisms (policy enforcement, output validation).
- Integrate AI services into APIs and applications.
- Collaborate with data engineers to ensure data quality and relevance.
Required Skills & Experience
- Strong Python engineering skills.
- Hands-on experience with LLMs and agent frameworks.
- Solid understanding of prompt engineering, embeddings, vector search.
- Experience deploying AI solutions on Azure.
- Experience with AI evaluation, testing, and monitoring.
Nice to Have
- Full-stack development experience.
- Familiarity with Responsible AI practices.
- Supply chain AI or analytics experience.
