Generative AI Applications Engineer (Agents & RAG)
Tasks
- Build CI/CD templates
- Build Retrieval Augmented Generation systems
- Define SLIs and SLOs
- Deliver in hybrid restricted and air gapped environments
- Design and ship agentic workflows
- Design prompts and policies
- Evaluate large language models
- Implement RAG retrieval pipelines
- Implement evaluation harnesses
- Implement safety and compliance guardrails
- Instrument metrics logs and traces
- Manage infrastructure as code with Terraform
- Optimize token usage and cost
- Run A/B experiments
- Run on call and conduct postmortems
- Select and optimize LLMs
- Ship SDKs and reusable platform components
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS Bedrock | Amazon Kendra | Azure OpenAI | B testing | CI/CD | Chroma | Data Governance | Docker | Document AI | Faiss | Gemini | Gemma | Generative AI | Google Vertex | Google Vertex AI | Incident Management | Infrastructure as Code | Kubernetes | LLM Evaluation | Langchain | Language Models | Large Language Models | Llamaindex | Observability | OpenSearch | PGVector | Pinecone | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | SLI | SLO | Security Compliance | Semantic Kernel | Terraform | Token optimization | Transformers | Vector Search | Vertex AI | Weaviate | Zero Trust | Zero Trust Architecture | “as-code”
Education
N/A
Regions
Countries
States
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