Senior AI Engineer (Fintech)

TL;DR

Senior AI Engineer (Fintech): Building and optimizing production-grade AI systems and LLM pipelines for a global financial operating system with an accent on RAG architectures, vector search, and financial data processing. Focus on implementing reliable, observable, and cost-efficient AI features like spend categorization and automated reconciliation.

Location: Remote (Must be based in Colombia or the LatAm region)

Company

hirify.global is a groundbreaking financial operating system providing corporate cards, cross-border payments, and spend management software for global businesses.

What you will do

• Design and maintain production-grade LLM integration pipelines including RAG, prompt engineering, and chain orchestration.
• Develop AI features for core financial products such as spend categorization, document extraction, and automated reconciliation.
• Build and optimize vector search pipelines using Pinecone, Weaviate, or pgvector to power semantic search.
• Deploy and monitor ML models in production, ensuring appropriate latency SLOs and detecting data drift.
• Integrate AI services with backend microservices using Python, Go, or Node.js.
• Collaborate with Product and Data Science teams to define the AI roadmap and translate requirements into reliable systems.

Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 5+ years of professional software engineering experience, with 3+ years focused on production AI/ML systems.
• Hands-on experience deploying LLM-powered applications using OpenAI, Anthropic, or Cohere APIs.
• Proficiency in Python and experience with AI orchestration frameworks like LangChain or LlamaIndex.
• Strong backend fundamentals including REST APIs, PostgreSQL, and cloud infrastructure (AWS, GCP, or Azure).
• Must be based in Colombia or the LatAm region.

Nice to have

• Experience in fintech or other regulated industries where AI reliability is critical.
• Familiarity with ML lifecycle management tools such as MLflow, Weights & Biases, Vertex AI, or SageMaker.
• Knowledge of real-time data streaming using Kafka or Kinesis for event-driven pipelines.
• Prior experience working in a startup or scale-up environment.