Overview
Engineer AI Platform builds, deploys, and supports reusable enterprise AI platform capabilities.
What you'll do
- Develop and maintain reusable AI platform services, APIs, SDKs, and automation patterns.
- Implement integrations with approved LLM services, AI gateways, orchestration frameworks, and vector/search services.
- Build and support CI/CD, infrastructure-as-code, automated testing, telemetry, and operational runbooks.
- Partner with architecture, cybersecurity, data, privacy, and solution delivery teams to meet enterprise controls.
- Troubleshoot incidents, reliability issues, performance bottlenecks, access issues, and environment defects.
- Document platform patterns, onboarding guidance, reusable components, and developer enablement materials.
What you'll need
- 1-5 years of experience building backend services, APIs, automation, cloud-native or platform services.
- Hands-on experience with Python and modern software engineering practices.
- Experience with Azure, Azure DevOps or GitHub Enterprise, CI/CD, containers, and Infrastructure as Code.
- Experience with logging, monitoring, and secure development practices.
- University/college education in computer science, engineering, data/analytics, business/technology, risk/governance, or related field (equivalent experience considered).
- Strong collaboration, documentation, problem solving, and operational support skills.
Nice to have
- Exposure to LLM application patterns, RAG, prompt orchestration, vector search, model evaluation, and AI observability.
Details
Read the full description and apply on the company’s own careers page.
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