Technical Engineer AI

About the 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 translates business requirements into scalable AI-driven products and services.

Key Responsibilities

• Story Specification: Translate business objectives and process requirements into detailed functional and technical designs, user stories, 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. Ensure compliance with enterprise architecture, security, governance, documentation, and coding standards.
• 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. Conduct root cause analysis for hallucinations, orchestration failures, and integration incidents.
• Project Support: Contribute to project deliverables in Agile, DevOps, or waterfall delivery models. Collaborate with project managers and stakeholders to ensure timely and high-quality delivery of AI solutions.

Requirements & Tech Stack

• Python development
• AI application engineering
• Enterprise integration technologies
• React.js
• Node.js
• REST APIs
• Orchestration frameworks
• Azure AI Foundry
• Azure OpenAI
• Azure AI Agent Service
• Semantic Kernel
• Retrieval-Augmented Generation (RAG) pipelines
• Vector databases
• Cloud-native application development
• CI/CD pipelines
• MLOps practices
• Model monitoring and observability tooling
• Automated testing
• DevOps delivery
• Agile ways of working

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 engineering profiles through 6+ years for advanced engineering and leadership-oriented levels.
• 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.
• Capability expectations include progression from supporting development activities and issue resolution to independently leading complex AI engineering initiatives, mentoring engineers, contributing to governance and safety standards, and driving enterprise AI transformation outcomes.