Why this role stands out
This hybrid AI Platform Engineer role offers a fantastic opportunity to grow your expertise in cutting-edge AI technologies within a reputable company. You'll thrive here if you have a solid foundation in cloud and DevOps, coupled with a passion for AI and a knack for problem-solving. Apply now to shape the future of AI platforms!
Quick overview
Job description
Required Skills:
- Approximately 2 - 4 years of professional experience in cloud, systems, platform, application, DevOps, automation, enterprise SaaS administration, technical support, or a closely related engineering discipline.
- At least one year of meaningful exposure to AI, intelligent automation, generative AI, or AI-enabled enterprise platforms; equivalent hands-on project experience may be considered.
- Hands-on experience with at least one major AI ecosystem and the ability to learn and support additional platforms.
- Working knowledge of APIs, identity/access concepts, cloud/SaaS administration, troubleshooting, change management, and technical documentation.
Education:
Bachelor's degree in Computer Science, Information Systems, Engineering, Cybersecurity, or a related technical discipline, or an equivalent combination of education and relevant professional experience.
Preferred Skills:
- Experience with OpenAI/ChatGPT Enterprise or Business, OpenAI APIs, Microsoft Copilot/Copilot Studio/Azure AI services, or Google Gemini/Vertex AI/Google Workspace.
- Experience supporting APIs, connectors, AI agents, retrieval-augmented generation (RAG), enterprise search, knowledge grounding, or related integration patterns
- Experience with PowerShell, Python, REST APIs, JSON, scripting, workflow automation, or low-code automation platforms
- Experience with Microsoft Entra ID, Google identity, IAM/RBAC concepts, service principals/service accounts, secrets, permissions, or access reviews.
- Familiarity with enterprise security, privacy, data-loss prevention, records/data handling, responsible AI, and AI governance requirements.
- Experience using IT service management practices for incident, request, change, problem, knowledge, and service operations.
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