Mission of the Role
We are looking for a skilled developer to build and maintain intelligent AI agents that automate banking processes. You will use python or n8n to create integrated workflows and Apache Airflow to orchestrate data pipelines, connecting LLMs securely to our banking systems to improve efficiency and customer experience.
Core Responsibilities
You will be responsible for designing, implementing, and optimizing AI-driven automation solutions:
1. Design & Build AI Agent Workflows:
· Develop LLM-based services for banking assistants and tools.
· Implement RAG systems to ground agents in accurate financial data and compliance rules.
· Use n8n to build multi-step automations that connect AI decisions to banking APIs and databases.
2. Orchestrate & Optimize AI Pipelines:
· Use Apache Airflow to schedule, monitor, and manage reliable data and model pipelines.
· Integrate voice AI components (ASR/TTS) to enable conversational banking features.
· Optimize agent performance through prompt engineering, caching, and batching strategies.
Skills & Qualifications
· Proficiency in Python and practical experience with ML frameworks (e.g., PyTorch, Transformers).
· Hands-on project experience building applications with LLMs (e.g., RAG, fine-tuning, or inference services).
· Proven experience with automation tools: Practical use of n8n and Apache Airflow to build and manage workflows.
· Software Engineering Fundamentals: Familiarity with Git, Docker, API integration, and CI/CD principles.
· Industry Awareness: Understanding of security, privacy, and compliance needs in the banking sector.
Preferred Qualifications
· Experience in creating custom nodes in n8n or building advanced DAGs in Airflow.
· Familiarity with vector databases (e.g., LanceDB, pgvector, FAISS) and optimizing LLM inference and fine-tuning/LoRA
· Knowledge of voice AI technologies (e.g., Whisper for ASR/TTS).