Senior Engineer - AI
Tasks
- Apply enterprise security and governance with Entra RBAC and Key Vault
- Automate model deployment
- Build production AI applications with CI CD
- Create feature stores
- Design AI solutions on Azure
- Design LLM evaluation and testing frameworks
- Develop RAG pipelines
- Develop agentic AI and GenAI workloads
- Embed Responsible AI practices
- Enable hybrid retrieval architectures
- Implement MLOps with Azure ML and Databricks
- Implement model monitoring for drift bias and quality
- Implement monitoring and observability
- Implement vector database solutions
- Improve LLM latency and cost
- Integrate data from ADLS Delta Lake EventHub Synapse and APIs
- Lead workshops and mentor engineers
- Optimize prompts
- Produce HLD and LLD
- Provision infrastructure with IaC
- Track experiments and manage model registry
Perks/Benefits
- Career pathways
- Hybrid work
- Inclusion and diversity
- Ongoing learning
- Remote work flexibility
- Work-life balance
Skills/Tech-stack
AI Search | AKS | Azure AI | Azure AI Search | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure DevOps | Azure Machine Learning | Azure Monitor | Azure Storage | Azure Synapse | Azure Synapse Analytics | Bicep | CI/CD | Data Lake Storage | Databricks | Delta Lake | Docker | Entra ID | Event Hubs | Experiment tracking | Feature Store | GitHub Actions | Grafana | Infrastructure as Code | Key Vault | Kubernetes | LLM Evaluation | Langchain | MLOps | Machine Learning | Microsoft Fabric | Model Registry | Observability | PGVector | Prometheus | Prompt engineering | Python | RAG | RBAC | Redis | Semantic Kernel | Synapse Analytics | Terraform | “as-code”
Education
N/A
Roles
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