Senior AI Engineer
Tasks
- Benchmark agent performance for reliability and cost efficiency
- Build multi-agent workflows
- Collaborate with product engineering security and business teams
- Conduct PoCs and deliver MVPs
- Create business logic guardrails
- Design AI feature requirements
- Design evaluation pipelines for AI features
- Develop Python AI services
- Document model usage and data flows
- Ensure EU AI Act compliance
- Implement AI orchestration pipelines
- Implement RAG and LLM evaluation
- Implement memory and state management for agents
- Implement observability for AI components
- Implement prompt injection prevention guardrails
- Integrate AI features into product flows
- Manage AI versioning and backward compatibility
- Monitor AI feature quality
- Monitor AI latency error rates drift signals
- Present AI limitations to customers and stakeholders
- Research LLM and RAG methods and vendors
- Translate DSML decisions into Jira tickets and documentation
- Translate procurement logic into structured prompts
Perks/Benefits
- 30 days vacation
- English as official language
- International team
- Remote-first
- Social activities
- Team building events
Skills/Tech-stack
AWS | Autogen | Azure | Chain-of-Thought | CrewAI | Docker | Drift Detection | Error Rate Monitoring | Error rate | FastAPI | GCP | Guardrails | Kubernetes | LLM Evaluation | Langgraph | Latency monitoring | Logging | Metrics | Monitoring | NLP | NLP evaluation | Observability | Plan-and-Execute | Prompt engineering | Python | RAG | REST APIs | Rate monitoring | React | Streaming | Vector Databases | Versioning
Education
Roles
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