Engineering Manager, D&T, Applied AI
Tasks
- Build and scale AI engineering capabilities including data pipelines and model integration
- Coach and retain engineering talent and develop technical leadership
- Drive end to end execution for AI use cases and workflows
- Drive engineering excellence with CI CD automated testing observability and reliable releases
- Ensure AI solutions are secure scalable governable and compliant
- Establish engineering culture for experimentation and production hardening
- Lead engineering teams delivering Applied AI products from idea to production
- Lead technical decision making for cloud native architectures and system integrations
- Make build vs buy decisions for models and AI platform components
- Operationalize responsible AI in regulated environments
- Partner cross functionally to identify and accelerate AI adoption
- Translate business priorities into AI engineering roadmap
Perks/Benefits
- Community volunteering
- Comprehensive health benefits
- Employee assistance benefits
- Growth and development programs
- Inclusive work environment
- Lifelong learning opportunities
- Sustainability initiatives
Skills/Tech-stack
API Services | Agentic Workflows | Agile delivery | Artificial Intelligence | Automated testing | Azure | Azure Data | Azure Data Factory | CI/CD | Cost Management | Data Factory | Databricks | Distributed Systems | Engineering Planning | Experiment tracking | Generative AI | Governance | Incident Management | LLMOps | Language Models | Large Language Models | MLOps | Microsoft Fabric | Model Evaluation | Model Monitoring | Observability | Prompt orchestration) | Retrieval-Augmented Generation | Security | Synapse | Telemtry | Vector Search | Workflow Orchestration
Education
Roles
Engineering | Engineering Leader | Engineering Manager | Manager
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