Senior AI Engineer - Freelance
Tasks
- Apply LLM as a judge for evaluation
- Build evaluation pipelines
- Build multi agent systems in production
- Build production AI observability
- Build voice agents
- Create golden datasets for evaluation
- Define evaluation strategies and measure regressions
- Design production AI systems end to end
- Evaluate model and system performance
- Implement LLM as judge online evaluations
- Implement STT and TTS pipelines
- Implement agent to agent communication
- Implement guardrail and latency metrics
- Implement human-in-the-loop patterns
- Implement offline evaluations
- Implement online quality monitoring
- Implement structured output reliability checks
- Implement tracing and prompt output logging
- Implement turn detection
- Implement vision language tasks
- Instrument conversational LLM systems in production
- Integrate orchestration frameworks
- Integrate tools and MCP
- Monitor latency and token usage
- Propose AI system architectures
- Run online deterministic evaluations
Perks/Benefits
- Agile collaboration
- Code review
- Continuous integration
- Flexibility
- Growth opportunities
- Internal knowledge base
- Knowledge sharing sessions
- Remote work
Skills/Tech-stack
Agent Orchestration | Agent systems | Amazon Bedrock | Conversational AI | Deterministic Evaluation | Evaluation Pipelines | Golden Dataset | Guardrails | LLM Evaluation | LLM-as-a-Judge | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Latency monitoring | MCP | Machine Learning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | Observability | Online monitoring | OpenAI API | Prompt logging | Python | STT | Span Attributes | Structured Output | TTS | Token Monitoring | Tool integration | Tracing | Turn Detection | Vision Language Models | Vision-language
Education
N/A
Roles
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