LLM AI Engineer
2 days ago
EXPERIENCE - 5 to 8 years
Key Responsibilities:
- Agent Orchestration: Design and implement complex agentic workflows using LangChain and LangGraph. Manage state, cyclic graphs, and decision-making loops for autonomous agents.
- LLM Evaluation (LLM-as-a-Judge): Build robust evaluation pipelines. specific code/prompts where a stronger model (e.g., GPT-4) acts as a judge to verify the accuracy, safety, and adherence of the application's responses against strict requirements.
- Model Optimization: Execute Prompt Tuning and advanced prompt engineering strategies to align model outputs with user needs. Manage invocation calls to various foundation models (OpenAI, Anthropic, Open Source).
- Data Integrity: Analyze input/output data streams to ensure strict adherence to project requirements and schema validation.
- Ownership: operate as a core independent contributor.
Required Technical Skills:
- Deep expertise in Python and the modern AI stack.
- Orchestration: Proven experience with LangChain; specific experience with LangGraph for multi-agent systems is highly preferred.
- Evaluation: Experience implementing "LLM-as-a-Judge" patterns, or similar evaluation frameworks.
- Fine-Tuning: Understanding of PEFT (Parameter-Efficient Fine-Tuning) and Prompt Tuning techniques.
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