Data and AI Engineer
Tasks
- Build and maintain scalable data pipelines for real time and historical data
- Build and optimize data infrastructure on Azure
- Build data pipelines
- Collaborate on end to end AI product delivery
- Conduct code reviews
- Contribute to AI product roadmap
- Design RAG architectures
- Develop autonomous or semi autonomous AI decision systems
- Ensure data quality reliability and low latency delivery
- Implement vector database solutions
- Integrate Large Language Models into workflows
- Participate in agile ceremonies
- Partner with business stakeholders to translate needs into AI solutions
Perks/Benefits
- Continuous learning resources
- Health and wellbeing benefits
- Hybrid work model
- Internal mobility
- Professional development programs
- Wellness programs
Skills/Tech-stack
21 CFR Part 11 | AI Safety | Agent systems | Annex 11 | Artificial Intelligence | Azure | Azure Event | Azure Event Hubs | CFR Part 11 | Data Engineering | Data Pipelines | Data Streaming | EU Annex 11 | Event Driven | Event Hubs | Event-driven architecture | Explainability | FDA 21 CFR | FDA 21 CFR Part 11 | Generative AI | GxP | Kafka | Language Models | Large Language Models | Machine Learning | Multi-Agent | Multi-Agent Systems | Part 11 | RAG | Real Time | Real-Time Data Streaming | Real-time Data | Responsible AI | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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