AI Platform Engineer
Skills
Azure Data FactoryComputer ScienceDevopsSoftware As A ServiceApplication ServicesDatabasesEnterprise Systems
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's degree in Computer Science Software Engineering Artificial Intelligence Data Engineering or related field
- 5+ years of experience in AI engineering machine learning engineering AI platform development or related technical roles
- Experience building and deploying AI-enabled applications AI services or customer-facing AI capabilities in production environments
- Strong proficiency in Python SQL REST APIs and AI service development
- Experience designing and deploying AI ML services using Azure Anthropic vector databases or related AI tooling
- Experience integrating AI capabilities into customer-facing web applications SaaS products or digital platform experiences
- Familiarity with scalable SaaS application architectures API integration patterns and AI orchestration workflows
- Familiarity with relational databases secure data access concepts and customer-aware data architectures
- Strong analytical systems-thinking and problem-solving capabilities
- Ability to clearly communicate technical concepts and AI solution designs to technical and non-technical stakeholders
- Ability to work independently and collaboratively within cross-functional teams including Backend Engineering Frontend Development DevOps Data Integrations and UI UX
- Willingness to travel occasionally approximately 10%
Nice to have
- Technical leadership
- Cross-functional collaboration
- Systems thinking
- Problem solving
- Clear communication
- Independent work
Day to day
- Design and build reusable AI platform services that power enterprise systems and customer-facing digital products.
- Develop AI orchestration, RAG pipelines, prompt management, vector search, and model integration frameworks for scalable deployment.
- Collaborate with cross-functional teams to operationalize secure cloud-native AI capabilities, improve digital experiences, and standardize AI service delivery.