MLOps Platform Engineer

dv01 is lifting the curtain on the largest financial market in the world: structured finance. The $16+ trillion market is the backbone of everyday activities that empower financial freedom, from consolidating credit card debt and refinancing student loans, to buying a home and starting a small business.

dv01’s data analytics platform brings unparalleled transparency into investment performance and risk for lenders and Wall Street investors in structured products. As a data-first company, we wrangle critical loan data and build modern analytical tools that enable strategic decision-making for responsible lending.  In a nutshell, we're helping prevent a repeat of the 2008 global financial crisis by offering the data and tools required to make smarter data-driven decisions resulting in a safer world for all of us. 

More than 400 of the largest financial institutions use dv01 for our coverage of over 100 million loans spanning mortgages, personal loans, auto, buy-now-pay-later programs, small business, and student loans. dv01 continues to expand coverage of new markets, adding loans monthly, and developing new technologies for the structured products universe.

 

YOU WILL:

Build and operate an AI infrastructure platform:
You will design, build, and operate cloud-native infrastructure and platform tooling that accelerates AI development across the company. This includes enabling teams to develop, deploy, and operate AI-powered services safely and efficiently in production environments.

Own the DevOps and infrastructure side of MLOps and Agentic Systems:
You will focus on the operational foundations of AI systems, including CI/CD for AI workloads, scalable inference infrastructure, observability, cost management, and reliability. You will establish repeatable patterns and shared services that reduce friction for teams building AI-enabled applications.

Enable AI services, agents, and runtime platforms:
You will build and maintain infrastructure to support AI services such as LLM-backed APIs, Model Context Protocol (MCP) servers, and agentic systems used by production applications. You will enable secure tool access, runtime orchestration, and isolation boundaries for AI-driven workloads.

Integrate MLOps capabilities into platform operations:
You will apply MLOps concepts to improve platform operations, including using AI-driven approaches for monitoring, alerting, anomaly detection, and incident response across AI and non-AI systems. You will help evolve how the platform observes and operates complex AI-enabled systems at scale.

Establish governance, security, and operational guardrails:
You will help define and implement infrastructure-level governance for AI systems, including access controls, deployment policies, auditability, and secure-by-default patterns. You will partner with security and compliance teams to ensure AI infrastructure aligns with organizational risk and regulatory requirements.

Provide technical leadership and enablement:
You will act as a technical leader, influencing platform architecture and best practices across teams. You will mentor engineers and work closely with product, data, and application teams to align AI platform capabilities with business goals.

YOU HAVE:

A senior cloud and platform engineer:
You have 8+ years of experience in cloud infrastructure, DevOps, or platform engineering roles, with deep expertise designing and operating distributed systems in production.

Experienced with MLOps and agentic platforms:
You have direct exposure to ML/GenAIOps practices, such as monitoring, anomaly detection, predictive alerting, or automated remediation, applied to real production systems. 5+ years of MLOps experience is required.

Strong in cloud-native infrastructure:
You are proficient in building and managing cloud environments, Kubernetes, containerized