Senior AI Engineer
Tasks
- Apply knowledge graphs for personalization
- Build Agentic AI workflows
- Build async data processing workflows
- Collaborate on AI product delivery
- Deploy AI pipelines
- Design scalable backend services
- Develop LLM based user experiences
- Implement RAG systems
- Implement feature flag based experimentation
- Monitor production systems
- Optimize API latency and token management
- Prototype and benchmark model outputs
- Set up automated evaluation metrics
Perks/Benefits
Skills/Tech-stack
API Latency | AWS | Agentic development | Celery | Cloud Computing | Datadog | Deep learning | Django | FastAPI | GCP | Grafana | Integration Testing | Kafka | Knowledge graphs | LLM APIs | Language Models | Large Language Models | LaunchDarkly | Machine Learning | OpenTelemetry | PostgreSQL | Prometheus | Prompt engineering | Python | RAG | REST APIs | Redis | Retrieval-Augmented Generation | SQS | Schema migrations | Sentry | SonarQube | System design | Token Management | Unit Testing
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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