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Tech Stack
Tools & technologiesAzurePython
About the role
Key responsibilities & impact- The AI Engineer is responsible for building, deploying, and operating production-grade AI and Agentic AI solutions across the enterprise.
- This is a hands-on engineering role focused on implementing LLM-powered applications, orchestration and multi-agent workflows, and secure API-driven integrations using Azure AI Foundry and Azure-native services.
- The role works across the full AI lifecycle —from system design and development to production operations—ensuring solutions are secure, scalable, observable, and governed.
- The AI Engineer partners closely with Engineering Leads, architects, data science teams, and platform/security stakeholders to translate AI use cases into reliable, enterprise ready systems.
Requirements
What you’ll need- A degree in Computer Science / Engineering or a related discipline; or equivalent work experience
- 10+ years in a Global IT environment working with multiple disciplines to deliver projects in line with customer needs
- 3+ Years Global delivery or transformation preferably in large scale infrastructure programs
- 3+ Years in a global operations environment
- Python Certification
- Azure AI Services
- Azure Data Services
Benefits
Comp & perks- Competitive salary
- Health insurance
- Flexible work hours
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI solutionsAgentic AILLM-powered applicationsAPI-driven integrationssystem designdevelopmentproduction operationsscalable solutionsobservable systemsgoverned systems
Soft Skills
collaborationcommunicationproblem-solvingproject deliverycustomer needs alignment
Certifications
Python Certification
