About this role
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. This role bridges functional and technical engineering to translate business requirements into scalable AI-driven products using Azure AI platforms, large language models, and orchestration frameworks. The position focuses on implementing secure, observable, and reliable AI ecosystems, including RAG pipelines and vector databases, while supporting modern UI development for AI-enabled applications. Responsibilities include troubleshooting model performance, hallucinations, and integration failures, as well as establishing AI evaluation criteria and human-in-the-loop controls.
Key Responsibilities:
- Story Specification: Translate business objectives and stakeholder requirements into detailed functional and technical designs, user stories, and implementation plans.
- Development & Delivery: Lead end-to-end delivery of enterprise AI initiatives, ensuring compliance with security, governance, and coding standards.
- Testing: Define and execute testing strategies for autonomous systems, reasoning loops, and AI safety guardrails.
- Incident Management: Monitor production AI environments, conduct root cause analysis for orchestration or model failures, and implement corrective actions.
- Project Support: Collaborate with cross-functional teams in Agile and DevOps environments to ensure timely delivery of AI solutions.
Qualifications
- Bachelor or Master degree in Computer Science, Information Technology, Artificial Intelligence, Software Engineering, Data Science, or a related discipline.
- Professional experience ranges from 0–1 years for entry-level profiles to 6+ years for advanced/leadership levels.
- Strong technical expertise in Python development and AI application engineering.
- Proficiency in Azure AI services, orchestration frameworks, React.js, Node.js, and cloud-native development.
- Experience with MLOps, CI/CD pipelines, model monitoring, and automated testing is required.