Software Engineer (Cloud Infrastructure)

Quantcast•Seattle, WA

3h•Hybrid

About The Position

At Quantcast, we don't just build advertising technology, we revolutionize how it works. Our AI-powered Demand Side Platform (DSP) connects the world's most ambitious marketers with their ideal audiences across the open internet, delivering results that actually move the needle. Since 2006, we've been the industry's trailblazer, launching the first AI-powered measurement platform for publishers and the first AI-driven DSP. Our AI doesn't just optimize—it delivers the measurable outcomes that matter most to our clients, giving them the competitive edge they need in a crowded marketplace. Ready to join the team that's defining the future of digital advertising? We are seeking a Software Engineer to join our Cloud Infrastructure team. This role focuses on building and automating cloud foundations that help engineering teams deliver software safely and efficiently. You will work closely with software and systems engineers to create reliable, scalable, and secure infrastructure supporting internal and customer-facing systems. The team develops and operates the cloud platforms, automation, and controls that enable Quantcast engineers to build and run software at scale. A curious new graduate who enjoys solving practical problems, learning how systems work, and turning repetitive work into reliable automation will thrive here.

Requirements

Recent graduate (0-1 years) with a Bachelor's Degree in computer science or equivalent experience.
You must be work-authorized in the United States without the need for current or future employer sponsorship. We are not currently able to engage candidates on OPT.
You must currently be based in the greater Seattle area, as part of the interview process will be in-person at our Seattle office.
Strong programming foundations in Python, Go, Java, or a similar language.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Familiarity with containerization tools such as Docker and Kubernetes.
Strong problem-solving and debugging skills.
Organized, collaborative, and eager to learn.

Nice To Haves

Familiarity with automation or infrastructure-as-code tools such as Terraform is a plus.
Interest in LLM-enabled coding tools, model APIs, or inference systems.
Linux, networking, identity, or security fundamentals are a plus.

Responsibilities

Contribute to cloud services, internal tools, and automation used by engineering teams.
Develop and operate cloud infrastructure, improving its reliability, security, and scalability.
Explore and help evaluate emerging cloud, AI, and model-inference technologies, and share useful findings with engineering teams.
Build automation that reduces manual work and makes infrastructure configuration safer and more consistent.
Help support cloud environments for LLM-powered developer tools and model inference workloads.
Write clean, maintainable, and well-tested code, and provide input into the team's roadmap.