Senior AI Engineer
Tasks
- Build automated evaluation pipelines
- Build tool using LLM agents
- Collaborate with product and domain experts to prototype AI workflows
- Create context engineering pipelines
- Define safety guardrails and fallback logic
- Design and ship production agentic AI systems
- Develop retrieval augmented generation workflows
- Document system behavior and failure modes
- Establish evaluation frameworks
- Implement multi-agent workflows
- Implement observability and analytics
- Integrate AI functionality into backend services and APIs
- Set up online monitoring metrics
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Agent systems | Agentic AI | Anthropic | Azure OpenAI | B testing | Backend Development | CI/CD | Context engineering | Cost Tracking | Embeddings | Evaluation Frameworks | Event Driven | Event-driven architecture | Fallbacks | Function Calling | Golden datasets | Google Gemini | Grounding | Human-in-the-loop | JSON Schema | LLM APIs | LLM-as-judge | Language Models | Large Language Models | Microservices | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | OpenAI | OpenTelemetry | Prompt versioning | Python | RAG | Regression testing | Retries | Retrieval-Augmented Generation | Safety Guardrails | Security | The Loop | Tool use | Tracing | Vector Databases | Vertex AI
Education
N/A
Roles
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