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: 10+ 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.