AI Infrastructure Engineer​/Financial Services​/Miami

A growing fintech company focused on modern financial services and trading technology is looking for an AI Infrastructure Engineer to build and operate the platform supporting its next generation of AI-powered financial workflows. The company combines financial services expertise with advanced data, AI, and engineering capabilities, with a strong focus on security, auditability, correctness, and reliability. The engineering environment is primarily built around the Microsoft Azure ecosystem and integrates closely with .NET-based

internal systems and sensitive financial data.

As an AI Infrastructure Engineer, you'll own the platform layer that turns advanced AI models into reliable, secure, and production-ready internal services. You'll design and operate infrastructure for both large-scale and specialized models, build secure APIs for AI-powered applications, manage GPU-based workloads across development and production, and integrate model serving with retrieval systems, databases, internal services, and authentication. This is a hands-on platform engineering role where you'll work closely with AI engineers to support fine-tuning, evaluation, and deployment while establishing standards for model packaging, versioning, rollout, and rollback.

You'll also play a key role in building the engineering infrastructure that allows AI systems to operate reliably s includes developing CI/CD pipelines, implementing observability across latency, throughput, errors, GPU utilization, and service health, and supporting batch, interactive, and evaluation inference workloads. The ideal candidate has a strong infrastructure or platform engineering background, is comfortable working across applications and underlying infrastructure, and enjoys solving complex problems involving performance, reliability, security, and cost optimization.

This is a full-time, hybrid position based in Miami, FL, with flexibility for partial work from home. You'll have the opportunity to work at the intersection of AI, cloud infrastructure, and financial technology while helping establish the platform standards and systems that will support the company's growing AI capabilities.

• 5+ years of experience in infrastructure, platform engineering, Dev Ops, SRE, or ML platform engineering
• Strong experience with Microsoft Azure
• Strong experience with Kubernetes, preferably Azure Kubernetes Service (AKS)
• Hands-on experience with Docker and containerized services
• Strong C# / .NET experience, particularly for internal service integration
• Good Python skills for automation, AI infrastructure, and scripting
• Experience building production APIs and internal developer platforms
• Experience with CI/CD pipelines, infrastructure as code, and observability
• Strong Linux skills
• Experience operating systems with high security and reliability requirements
• Ability to debug complex issues across applications, infrastructure, networking, and storage

• Experience working with GPU clusters or distributed compute environments
• Experience serving large language models or other deep learning models in production
• Experience with high-throughput batch processing
• Familiarity with model registries, MLflow, or Azure Machine Learning
• Experience with financial services infrastructure or secure internal platforms in regulated environments
• Experience with retrieval-augmented generation systems, vector databases, or search infrastructure
• Experience optimizing latency-sensitive services and workloads

• Design and operate infrastructure for large-scale and specialized AI models
• Build secure internal APIs supporting AI-powered applications
• Deploy and manage GPU-based workloads…