Infrastructure Engineer @ Varick Agents

ABOUT VARICK

Varick builds AI agents that take over real operational workflows inside the world's largest enterprises. Our forward-deployed engineers and strategists embed with client teams to map how work gets done and build POCs, then our engineers bring those agents into production. We're venture-backed, revenue-generating from day one, and already in production inside several of these companies. You'll join an elite team from Meta, AWS Bedrock, Citadel Securities, McKinsey, BCG, Stanford, and more.

ABOUT THE ROLE

Our agents work inside real business operations: reconciling accounts, resolving invoice exceptions, and producing cash forecasts. These systems need to work reliably, and when something goes wrong, we need to understand what happened and be able to fix it.

You'd own the infrastructure that lets our engineers build, deploy, and operate agents across customer environments. You'd work closely with the people shipping those systems, understand where they're getting stuck, and build things that make their work easier. We're looking for an engineer who cares about getting that foundation right.

Our engineering team is small and moves quickly, led by Thomas Le Jeune, formerly an engineering leader at Dropbox. The other engineers have each built their own startups focused on post-training and reinforcement learning environments, with backgrounds at Stanford, Amazon, and Waterloo. Our co-founder and CEO, Vas Moza, was an engineer at Meta before starting Varick. Daniel Kornum, our Head of FDE, previously served as COO at Citadel Securities. You'd work with all of them directly.

WHAT YOU'LL DO

Make workflows reliable. Scheduling, retries, checkpointing, and recovery when a run fails halfway through. Retrying a workflow should never mean posting the same invoice twice

Make deployment straightforward. CI/CD, customer environments, secrets, and access controls. Engineers should be able to ship confidently and know how to recover when a deployment goes wrong

Keep the data layer working as we grow. Schema design, query performance, and knowing when Postgres is enough or when a workload needs something else

Make it clear what happened. Logs and traces that let us follow a run across agents and external systems, investigate a failure, or answer a customer's question months later

Handle unreliable integrations. Systems like NetSuite, Oracle, and Salesforce come with rate limits, partial failures, and their own ideas about availability. Our infrastructure needs to account for that

Operate what we build. Share on-call, respond to incidents, and follow through on fixes that prevent the same problem from happening again

Decide what needs a shared solution, what can stay simple, and what isn't worth building yet

WHAT WE'RE LOOKING FOR

We want to work with people who love technology and care about what it makes possible for others. For this role, that includes caring about the engineer using your deployment tools as much as the customer relying on the system. Our bar is the same for every engineering role:

You've owned something in production that other people depended on, and you were the one dealing with it when it broke

You keep up with technology out of genuine interest, not obligation. You try new tools, form opinions from using them, and rethink how you work when you find something better

You've changed someone's mind about a technical decision with evidence, and you've had your own mind changed the same way

You've operated software that other people depended on. You know what it's like to investigate a production failure with incomplete information, make a careful fix, and come back later to address the underlying problem

HELPFUL EXPERIENCE

Databases, distributed systems, and production operations

Workflow orchestration, queues, and idempotent job design

Integrations with enterprise systems such as NetSuite, Oracle, or Salesforce

You don't need to have used every tool we use. We care about your understanding of the fundamentals and your judgment about how much complexity a problem actually needs.