Principal Engineer – Generative AI & LLM Platforms
USD 153K-315K (estimate) Senior-level Full Time
Tasks
- Build LLM evaluation guardrails and safety mechanisms
- Define technical strategy and multi year product roadmap
- Deliver agile prototyping and productization
- Design production grade LLM and agentic solutions
- Design scalable low latency multi tenant distributed systems
- Develop generative AI and LLM platform architecture
- Establish observability SLOs incident response and cost management
- Evaluate emerging technologies for customer focused innovation
- Implement prompt engineering fine tuning and model customization
- Provide technical leadership mentoring and cross team influence
Perks/Benefits
Skills/Tech-stack
AI red teaming | AI/ML Services | AWS | AWS AI | AWS AI/ML | AWS AI/ML services | Adversarial Testing | Agents | Amazon Aurora | Amazon Aurora PostgreSQL | Amazon Bedrock | Amazon EKS | Amazon EMR | Amazon S3 | Apache Flink | Apache Spark | Aurora PostgreSQL | Batch inference | Bias | CI/CD | Capacity Planning | Content Safety | Cost Optimization | Distributed Systems | Embeddings | Experiment tracking | Explainability | Fine Tuning | Golang | Guardrails | Hugging Face | Hugging Face Transformers | Hybrid Cloud | Incident Response | Infrastructure as Code | Kubernetes | LLMOps | Langchain | Langgraph | Llamaindex | ML services | MLOps | Model Evaluation | Model Registry | Network Security | Observability | PGVector | Performance | Privacy | Prompt engineering | PyTorch | Python | RAG | Red Teaming | Regulatory Compliance | Reliability | Routing and Switching | SLOs | Safety | Scalability | Security | Semantic Caching | Streaming inference | Tokenization | Tool-Calling | Transformer | VPC | Version Management | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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