Architect, Data & AI
Tasks
- Apply DataOps and AIOps practices for pipeline optimization
- Architect AI and ML workloads with Azure Machine Learning
- Build RAG pipelines and tune retrieval latency
- Define architecture for enterprise data modernization
- Design agentic AI workflows for data discovery and preparation
- Design scalable batch and streaming data pipelines
- Ensure Responsible AI governance by default
- Establish observability monitoring and quality gates
- Implement secure coding and test driven development standards
- Integrate large language models into data engineering tasks
- Lead end-to-end delivery of complex projects
- Lead pre sales solutioning estimations and proposals
- Mentor and review cross functional engineering teams
- Oversee database performance and capacity planning
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | AI Search | AIOps | Agentic AI | Agile | Alerting | Apache Spark | Azure | Azure AI | Azure AI Search | Azure Cosmos | Azure Cosmos DB | Azure Data | Azure Data Factory | Azure Machine Learning | Azure OpenAI | Azure OpenAI Service | Azure SQL | Azure Synapse | Azure Synapse Analytics | By Design | CI/CD | Capacity Planning | Cloud Architecture | Cosmos DB | Data Architecture | Data Factory | Data Management | DataOps | Databricks | DevOps | Enterprise Data | Enterprise Data Management | Execution Plan | Execution Plan Analysis | HDInsight | Hadoop | Hive | Indexing | Kafka | LLM | LLM-Ops | Machine Learning | MariaDB | Microsoft Purview | Monitoring | MySQL | Observability | OpenAI Service | Oracle | Performance Engineering | Plan analysis | PostgreSQL | Query Tuning | RAG | Responsible AI | Retrieval-Augmented Generation | SLA management | SLAs | SLO | SQL Query Tuning | SQL Server | SQL query | Scrum | Security by design | Snowflake | Synapse Analytics | Teradata | Test-Driven | Test-Driven Development
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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