Senior AI Software Engineer
Tasks
- Apply safety guardrails
- Architect AI platform capabilities
- Build production services for tool calling
- Define service boundaries and APIs
- Design scalable agentic AI systems
- Develop vector retrieval and multi agent coordination
- Enforce policies and evaluation in workflows
- Establish AgentOps and LLMOps practices
- Implement model serving and inference systems
- Implement prompt and tool versioning
- Implement secure secrets and identity integration
- Integrate Model Context Protocol MCP
- Integrate agents with enterprise APIs and cloud services
- Manage AI workflow state and consistency
- Optimize distributed services for low latency and high throughput
- Perform performance reliability and security operations
- Run regression testing and experiments
- Set up tracing monitoring and evaluation suites
Perks/Benefits
- 401k match
- Dental insurance
- Health insurance
- Life insurance
- Long-term disability
- Paid Holidays
- Paid parental leave
- Paid sick leave
- Paid time off
- Short-term disability
- Vision insurance
Skills/Tech-stack
Access Management | Agentic AI | C++ | Cloud Computing | Distributed Systems | Docker | Evaluation | Experimentation | GPU Optimization | GRPC | Go | High Throughput | High-Throughput Systems | Identity and Access Management | Identity and access | Inference Optimization | Java | JavaScript | Kubernetes | Language Models | Large Language Models | Linux | Long Context | Low Latency | Low-Latency Systems | Machine Learning | Model Serving | Monitoring | Multi-tenant | Multi-tenant architecture | NoSQL | Observability | Prompt engineering | Python | REST | Regression testing | SLI | SLO | SQL | Secrets management | Security | Tenant architecture | Tool-Calling | Tracing | Vector Databases | Vector similarity | Workflow Orchestration
Education
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