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Stuut · 23 hours ago

Artificial Intelligence Engineer

San Francisco Bay Area

Full-time

Hybrid

Senior Level

4+ years exp

Stuut is an engineering-driven company revolutionizing B2B financial operations through cutting-edge AI technology. They are seeking an exceptional Senior/Staff AI Engineer to drive the development of core AI systems and infrastructure, focusing on building and scaling AI capabilities for financial applications.

Artificial Intelligence (AI)Financial ServicesFinTechSoftware

Responsibilities

Design and implement production-grade AI systems, including RAG pipelines, fine-tuning workflows, and MLOps infrastructure

Lead the development of intelligent systems for invoice matching, payment reconciliation, and financial document processing

Architect and build scalable data pipelines to support AI model training and inference

Develop and implement AI planning systems for automated financial workflows

Drive technical decisions around model selection, fine-tuning strategies, and system architecture

Collaborate with product and engineering teams to integrate AI capabilities into our core platform

Establish best practices for model evaluation, monitoring, and performance optimization

Contribute to building a strong AI engineering culture

Qualification

AI/ML technologiesLarge Language ModelsMLOpsPython programmingData pipeline developmentBackend systems developmentDistributed systemsCloud platformsContainerizationTechnical communicationDocumentation

Required

4+ years of software engineering experience, with at least 2 years focused on building production AI systems

Extensive experience with modern AI/ML technologies, including: Large Language Models (LLMs) and fine-tuning, Retrieval Augmented Generation (RAG), MLOps and model deployment, Vector databases and efficient retrieval systems

Strong programming skills in Python and experience with AI frameworks (PyTorch, TensorFlow, etc.)

Proven track record of building and deploying large-scale AI systems in production

Deep understanding of ML infrastructure, including training pipelines and serving architectures

Experience with data pipeline development and large-scale system integration

Strong background in backend systems development and distributed systems

Excellence in technical communication and documentation