Software Engineer - Infrastructure (Mid

About the role

The team designs and scales secure compute infrastructure for an applied AI lab. This role owns reliability, performance, and security for multi-tenant container platforms. The focus is on cloud environments where Julius runs code for over one million users.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

What you'll do

Deploy cloud resources using Helm and Terraform with SSO, network controls, and audit logging for access and compliance.

Drive observability through metrics, traces, and logs, define clear SLOs, and lead incident response when issues arise.

Optimize container images, scheduling, networking, and cost, and build fair-use and rate-limiting controls to manage shared compute.

Requirements

Production Kubernetes and container internals, including Docker and containerd, with strong networking fundamentals.

Cloud platform experience across AWS and GCP, plus infrastructure as code using Terraform and Helm for deployment automation.

Monitoring and logging proficiency with Prometheus, Grafana, OpenTelemetry, and ELK or Vector for telemetry and analysis.

Security best practices for containerized, multi-tenant systems to isolate workloads and protect infrastructure.

Practical notes

The role is based in San Francisco, California.

You will join a small, senior-led team handling massive infrastructure scale.

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Good to know

Infrastructure roles of this type rely on deep container and networking knowledge in cloud environments.

Platforms such as Kubernetes, Terraform, Helm, Prometheus, Grafana, and OpenTelemetry are common in modern compute platforms.

Techniques like autoscaling, GPU scheduling, and serverless abstractions are often explored to handle variable load.

Building side projects involving AI tools is common for engineers in applied AI labs.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

Career growth

Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.