Senior AI Engineer
Tasks
- Apply AI safety and responsible AI practices
- Build agentic systems
- Build data pipelines and training workflows
- Collaborate with product engineering and data teams
- Conduct code reviews and design discussions
- Debug production issues and improve scalability
- Deploy AI systems to production environments
- Deploy containerized services using Docker and Kubernetes
- Design AI architecture decisions
- Design build and deploy machine learning models end to end
- Develop and integrate APIs with internal and third party services
- Develop evaluation and observability for LLM apps
- Implement retrieval-augmented generation pipelines
- Lead feature ownership end to end
- Monitor AI systems for drift and reliability
- Optimize AI costs using token economics caching and routing
- Optimize models for performance accuracy and efficiency
- Translate technical tradeoffs for non specialists
Perks/Benefits
- N/A
Skills/Tech-stack
AI Safety | API Development | AWS | AWS GenAI | Agentic Systems | Artificial Intelligence | Caching | Data Pipelines | Docker | Embeddings | Evaluation Frameworks | Generative AI | Injection Defense | Kubernetes | LLM | Machine Learning | Model Optimization | Model routing | Monitoring | Observability | PII handling | Prompt injection | Prompt injection defense | Python | Quantization | RAG | Responsible AI | Retrieval-Augmented Generation | Token Economics | Training workflows | Vector Databases | Vector Search
Education
N/A
Roles
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