Senior AI Engineer
Tasks
- Build agentic systems
- Build data pipelines and training workflows
- Collaborate on code reviews and design discussions
- Containerize services with Docker
- Debug production AI issues
- Deploy applications on Kubernetes
- Deploy models to production
- Design AI architecture and tradeoffs
- Design ML AI models end to end
- Develop APIs for internal and third party integration
- Develop evaluation frameworks for models
- Ensure AI safety and responsible AI
- Handle PII in AI systems
- Implement caching and model routing
- Implement retrieval-augmented generation pipelines
- Mitigate prompt injection attacks
- Monitor model drift and reliability
- Optimize models for performance accuracy efficiency
- Optimize token economics and costs
- Set up observability for LLM apps
- Use quantization to reduce costs
Perks/Benefits
- N/A
Skills/Tech-stack
AI Safety | API Development | AWS | Agentic Systems | Amazon Web Services | Artificial Intelligence | Caching | Chunking | Data Pipelines | Docker | Embeddings | Evaluation Frameworks | Generative AI | Injection Defense | Kubernetes | LLM apps | Machine Learning | Model Drift | Model Monitoring | Model Optimization | Model routing | Observability | PII handling | Prompt engineering | Prompt injection | Prompt injection defense | Python | Quantization | RAG | Responsible AI | Retrieval-Augmented Generation | Token Economics | Training workflows | Vector Databases | Vector Search | Vector storage | Web Services
Education
N/A
Roles
AI Engineer | Engineer | Senior AI Engineer | Software Engineer
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