Applied AI Engineer

Responsibilities:
Design and deploy advanced multi-agent pipelines for credit analysis.
Optimize inference and prompt chains using frameworks like DSPy, GEPA, and LangChain.
Implement reasoning techniques (CoT, ToT, GoT) and evaluation systems (LLM-as-a-judge).
Develop ETL workflows, data pipelines, and observability dashboards.
Manage memory, retrieval, and orchestration in multi-agent systems.
Maintain cloud-based AI services and integrate with DevOps pipelines.
Qualifications:
5+ years in Python or JS development.
Proven experience with production-grade Agentic AI or reasoning systems.
Strong background in LLM Ops, data engineering, and cloud platforms (AWS/Azure).
Expertise in prompt engineering, RAG, HITL, and multi-agent control.
Nice-to-have:
Experience with RLHF/RLAIF or fine-tuning (LoRA/QLoRA).
Familiarity with graph data models.

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