Senior Principal AI Engineer
Tasks
- Architect LLM orchestration and abstraction layers
- Architect data and feature pipelines
- Build evaluation and observability strategy
- Conduct red teaming for AI systems
- Define enterprise model training strategy
- Design MCP servers and tool surfaces
- Design training data sourcing cleaning versioning governance
- Fine-tune large language models
- Implement retrieval augmented generation systems
- Implement safety and responsible AI guardrails
- Mentor and grow engineers
- Optimize AI workload cost performance scalability reliability
- Set multi year AI technical vision
- Train fine tune and evaluate machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | Agent systems | Artificial Intelligence | Chunking | Cloud Computing | Cloud Native | Cloud Native Architecture | Compliance | Cost Optimization | Data Governance | Data Pipelines | Dataset versioning | Distributed Systems | Distributed Training | Embeddings | Feature Engineering | Fine Tuning | Guardrails | Hybrid search | Inference Optimization | Language Models | Large Language Models | LoRA | Machine Learning | Model Evaluation | Observability | Orchestration | PEFT | PII handling | QLoRA | Quantization | Re-ranking | Red Teaming | Retrieval-Augmented Generation | SDK development | Token Cost | Token Cost Optimization | Tracing | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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