Senior AI Engineer

💻 Remote | LatAm - WE ARE EXCLUSIVELY CONSIDERING APPLICATIONS FROM INDIVIDUALS  CURRENTLY RESIDING IN LATAM. ❗️ONLY ENGLISH RESUMES WILL BE CONSIDERED 🗣️ PLEASE NOTE THAT THIS ROLE REQUIRES ENGLISH PROFICIENCY (C1-C2 LEVEL) About Motum Motum connects experienced developers, engineers, and technical professionals with US companies building committed, long-term tech teams. Our roles are fully remote and full-time, designed for people who want real ownership, meaningful work, and the opportunity to grow inside US-based dynamic teams. When you join Motum, you work full-time with one company, integrate directly into their team, and build a career with long-term impact. Ready to join us? About the Client Our client is a fast-growing US fintech AI company building intelligent software for modern financial teams. Its platform brings together financial, operational, and customer data to help companies automate complex workflows, identify risk, and make faster decisions. The team is now expanding its AI capabilities across document intelligence, financial research, data retrieval, and workflow automation. You will join a small product-focused engineering team where AI is a core part of the product rather than an experimental feature. Your work will move directly into production and be used in high-trust financial workflows where accuracy, security, and reliability matter. About the Role We are looking for a Senior AI Engineer to design, build, and operate production-grade LLM applications and AI agents. You will develop retrieval and knowledge systems, connect language models to financial data and external tools, and create agent workflows that can complete complex tasks reliably. You will also establish the evaluation, observability, and security practices needed to run these systems in a fintech environment. This role is best suited to an engineer who has already shipped generative AI features into production and understands the difference between a successful prototype and a dependable product. Responsibilities Build production LLM applications for financial research, document processing, decision support, and workflow automation Design RAG pipelines using document ingestion, chunking, metadata filtering, embeddings, reranking, and hybrid search Develop AI agents that use APIs, databases, internal services, and external tools to complete multistep tasks Implement structured outputs, tool calling, memory, state management, retries, and human approval flows Build evaluation suites for retrieval quality, factual accuracy, task completion, latency, and cost Create safeguards for hallucinations, prompt injection, sensitive financial information, and unauthorized tool access Design and maintain Python services using FastAPI and PostgreSQL Deploy, monitor, and improve AI workloads in a cloud environment Collaborate directly with product managers, engineers, and company leadership Review architecture decisions…