Senior Infrastructure Engineer

Rational Dynamics•Berkeley, CA

About The Position

Rational Dynamics builds customized AI reasoning systems for tasks of high cognitive complexity. Our initial market is the world’s leading institutional asset owners. We work very closely with these customers to create specialized, rigorous benchmark datasets encompassing their most valuable and difficult knowledge work. Then we use the benchmarks to construct agentic large reasoning models, applying the same rigor to prove that the models correctly do the work. Customers access the models through a tailored application service, making their most skilled, expensive workers dramatically more productive. We are an early-stage startup. Our founders previously started Voleon, now one of the world’s largest systematic investment managers, and recognized as a longstanding industry leader in applied machine learning. They bring to Rational Dynamics the same research discipline and data-driven focus that succeeded in the unforgiving, high-stakes setting of financial markets. We are looking for entrepreneurial researchers and engineers who want to work on cutting-edge agentic AI methods and build out a best-in-class core technical infrastructure. Our work environment is highly collaborative. Your colleagues will be accomplished experts in AI/ML, statistics, and systems engineering. As a Senior Infrastructure Engineer, you will design and build cloud infrastructure that powers Rational Dynamics' AI platform and customer deployments. Reporting to the Director of Software Engineering, you will join a small, fast-moving team. Your job is to build high impact systems to accelerate our systems that accelerate research and customer deployments across domains including model training, data acquisition and curation, cloud orchestration, and security. You will also flex beyond pure infrastructure when the situation calls for it, supporting research iteration, customer deployments, and security needs as they arise. This role is a means to make a difference: the infrastructure you build and maintain will determine whether Rational Dynamics can deliver high cognitive complexity systems that enterprises trust to drive their most critical workflows. We are building a team of people motivated by the future of speed and productivity that will be unlocked that agentic AI will unlock high complexity domains.

Requirements

Proven experience designing and deploying reliable production infrastructure
5+ years of experience designing and operating cloud infrastructure in production across multiple cloud providers (AWS, GCP, Azure)
Strong command of Kubernetes, Terraform, and modern CI/CD tooling
Security-conscious mindset with experience navigating enterprise compliance requirements such as SOC 2, PCI, DSS, or equivalent
Strong programming skills, with experience building infrastructure tooling in Go or an equivalent systems language
Familiarity with data pipeline tooling for batch and long-running workflows (e.g. Airflow, Temporal, etc.)
Comfort operating on a small team with dynamic requirements, threading the needle of speed and scalability, willing to take any task critical to customers and the team

Nice To Haves

Prior experience in a regulated or high-consequence industry such as finance, healthcare, or defense strongly preferred
Experience supporting GPU or ML-specific infrastructure workloads
Experience deploying solutions in enterprise customer cloud environments
Experience building infrastructure for the training and deployment of AI agents
Prior early-stage or small-team experience where you made critical end-to-end infrastructure decisions

Responsibilities

Own, extend, and improve cloud infrastructure that powers both production customer systems and internal research platforms, including compute, networking, storage, and deployment environments
Build and maintain CI/CD pipelines, developer tooling, and observability that keep the team shipping fast and catching problems early
Support GPU workloads and ML infrastructure needs in close collaboration with the research & ML team
Drive security posture and compliance efforts, including standards relevant to enterprise customers such as SOC 2
Build deployment and operations infrastructure that enables Forward Deployed Engineers to reliably build solutions quickly in heterogeneous enterprise cloud environments
Make pragmatic, well-reasoned infrastructure decisions that balance speed now with scalability later
Continuously improve system reliability, deployment simplicity, uptime, and cost efficiency through monitoring, feedback loops, and disciplined engineering