Agentic AI Engineer - LLM Models
First seen by Alion on Nov 14, 2026.
Job Purpose :
The IT Engineer - Agentic AI Engineer is responsible for designing, developing, deploying, and continuously optimizing enterprise-grade Agentic AI and intelligent automation solutions across global business environments.
The role combines the responsibilities of Functional Engineer AI and Technical Engineer AI to translate business requirements into scalable AI-driven products and services using Azure AI platforms, large language models, orchestration frameworks, and modern application technologies.
Key Activities :
- Story specification: Translate business objectives, process requirements, and stakeholder expectations into detailed functional and technical designs, user stories, acceptance criteria, and implementation plans for agentic AI and intelligent automation initiatives.
- Development & delivery: Lead and support the end-to-end delivery of enterprise AI initiatives using Azure-native AI services, orchestration frameworks, APIs, RAG architectures, and modern application technologies.
- Testing: Define and execute testing strategies for autonomous systems, reasoning loops, AI safety guardrails, and enterprise integrations.
- Incident management: Monitor production AI environments for performance, security, reliability, and compliance issues.
- Project support: Own and contribute to project deliverables in Agile, DevOps, or waterfall delivery models.
Tech Stack & Requirements :
- Strong technical expertise in Python development, AI application engineering, and enterprise integration technologies.
- Working knowledge of React.js, Node.js, REST APIs, orchestration frameworks, Azure AI Foundry, Azure OpenAI, Azure AI Agent Service, Semantic Kernel, Retrieval-Augmented Generation (RAG) architectures, vector databases, and cloud-native application development.
- Experience with CI/CD pipelines, MLOps practices, model monitoring, observability tooling, automated testing, DevOps delivery, and Agile ways of working.
- Ability to evaluate AI model quality, implement human-in-the-loop controls, troubleshoot hallucinations and reasoning failures, and optimize enterprise AI solutions for performance, security, and scalability.
- Bachelor or Master degree in Computer Science, Information Technology, Artificial Intelligence, Software Engineering, Data Science, or a related discipline.
Skills
Artificial Intelligence, Python, Azure, Generative AI, RAG, LLM, ETL, SQL