AI/ML Infrastructure Software Development Engineer
USD 86K-198K Senior-level Full Time
Tasks
- Build RAG and knowledge pipelines
- Build and maintain CI/CD deployment automation
- Conduct incident response and debugging
- Design and evolve LLM orchestration and multi model routing
- Enforce coding standards conduct code reviews and documentation
- Implement A2A communication patterns
- Implement agentic and protocol infrastructure for tool calling
- Implement fallback and degradation patterns
- Implement monitoring alerting logging tracing SLOs
- Implement safety monitoring and guardrails
- Implement secrets management
- Manage cost and token economics for LLM providers
- Mentor engineers and support secure compliant system design
- Own backend infrastructure components for AI ML models on Azure
- Perform ingestion indexing embedding semantic search and evaluation
Perks/Benefits
Skills/Tech-stack
API Design | API Management | Access Management | Alerting | Async Programming | Audit Logging | Authentication | Authorization | Azure Entra | Azure Entra ID | Azure Functions | Azure OpenAI | Azure OpenAI Service | CD pipelines | CI/CD | CI/CD pipelines | Container Apps | Cost Optimization | Data Pipelines | Distributed Systems | Docker | Embeddings | Entra ID | Evaluation | Fallback strategies | Identity and Access Management | Identity and access | Incident Response | Indexing | Infrastructure as Code | Input validation | Kubernetes | LLM integrations | LLM orchestration | Logging | Microsoft Azure | Model routing | Monitoring | Multi Provider LLM Integrations | Multi provider | Multi-model | Multi-model routing | OAuth2 | OpenAI Service | OpenID Connect | Output Sanitization | Python | RAG | Rate Limiting | Responsible AI | SLO | Safety monitoring | Secrets management | Semantic Search | Token Economics | Tracing | “as-code”
Education
Regions
Countries
States
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