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.