Senior AI Engineer
Tasks
- Build AI powered product and internal solutions using LLMs and RAG
- Build transaction and document classification and knowledge assistants
- Contribute to AI platform and tooling decisions for reuse speed and consistency
- Design quality and evaluation frameworks for AI systems
- Develop inference pipelines optimizing latency cost security and observability
- Experiment with AI models and tools and improve systems through failure analysis
- Implement fraud detection and operational automation
- Integrate AI into backend and product workflows
- Own AI systems end to end problem framing architecture implementation evaluation deployment monitoring and iteration
Perks/Benefits
- Hybrid work option
- Relocation support
- Remote work flexibility
- Stock options
- Travel support
- Work and Swim program
Skills/Tech-stack
APIs | AWS | Agents | Azure | Cloud infrastructure | Cost Optimization | Docker | Fine Tuning | GCP | Guardrails | Kubernetes | LLM Evaluation | Language Models | Large Language Models | Latency optimization | Model Fine-tuning | NoSQL | Observability | Prompt engineering | Prompting | Python | Python Software Engineering | RAG | Retrieval-Augmented Generation | SQL | Security | Software Engineering | Structured outputs | Tool-Calling | Vector Databases
Education
N/A
Roles
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