Senior Engineer- AI
Tasks
- Apply enterprise security and governance
- Automate deployment
- Build hybrid retrieval architectures
- Build production grade applications with CI CD
- Deliver Agentic AI and GenAI workloads
- Design AI solutions on Azure
- Design evaluation and test frameworks
- Develop RAG pipelines
- Implement AI monitoring and observability
- Implement MLOps workflows
- Implement infrastructure-as-code
- Integrate data using ADLS Delta Lake EventHub Synapse and APIs
- Lead workshops and mentor engineers
- Manage model registry and feature stores
- Optimize prompts and LLM evaluation
- Produce high level and low level design documents
- Set up model monitoring for drift bias quality
Perks/Benefits
- Career pathways
- Inclusion and diversity
- Mentorship
- Ongoing learning
- Remote/hybrid work
- Supportive workplace
- Work from home flexibility
Skills/Tech-stack
AI Search | AKS | APIs | Access Control | Azure | Azure AI | Azure AI Search | Azure DevOps | Azure ML | Azure Monitor | Azure Storage | Azure Storage ADLS | Bicep | CI/CD | Data integration | Databricks | Databricks Delta | Databricks Delta Lake | Delta Lake | Docker | Entra ID | Evaluation Frameworks | EventHub | Experiment tracking | Feature Store | GitHub Actions | Grafana | Infrastructure as Code | Key Vault | Langchain | MLOps | MLflow | Model Registry | PGVector | Power BI | Prometheus | Python | RAG | RBAC | Redis | Role-Based Access | Role-Based Access Control | Semantic Kernel | Synapse | Terraform | Vector Databases | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Senior AI Engineer
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