AI Engineer
Tasks
- Apply governance and safety guardrails
- Build Retrieval Augmented Generation systems
- Build internal tooling for eval and deployment
- Build tool-using agents
- Collaborate with product and domain experts
- Create automated evaluation pipelines
- Create multi-agent workflows
- Design Agentic AI systems
- Design safe tool execution workflows
- Develop backend AI services and APIs
- Develop context engineering pipelines
- Ensure reliability security and performance
- Establish evaluation frameworks
- Implement observability and analytics
- Implement structured function calling
- Integrate AI into cloud microservices and event systems
- Integrate LLM API capabilities
- Monitor online quality and safety metrics
- Prototype and iterate using measurable evals
- Run A/B experiments
- Ship production AI workflows
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Adversarial Testing | Agent systems | Airflow | Anthropic API | Azure OpenAI | CI/CD | Celery | Context Budgeting | Context Summarization | Cost Optimization | Datadog | Embeddings | Evaluation | Event Driven | Event-driven architecture | Function Calling | Golden datasets | Google Gemini | Grounding | Human-in-the-loop | Injection Defense | LLM APIs | Langfuse | Latency optimization | Microservices | Multi-Agent | Multi-Agent Systems | Observability | OpenAI API | OpenTelemetry | PII handling | Planning | Prompt injection | Prompt injection defense | Prompt versioning | Python | RAG | Regression testing | Replanning | Retrieval strategies | Retrieval-Augmented Generation | Safety Guardrails | Schema Validation | Search | Security | Temporal | The Loop | Tool use | Tracing | Vector Databases | Vertex AI | Workflow Orchestration
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Software Engineer
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