Staff Production Engineer

Description

The company runs the largest live shopping platform in North America and Europe, where people buy, sell, and discover items across hundreds of categories, from trading cards and fashion to electronics and live plants.

Sellers run real businesses on the platform. The company is building live commerce at a scale that has not been attempted in the West, with no existing model to follow, and the team is helping shape a new industry.

The team is fully remote but co-located, with hubs in the US, UK, Ireland, Poland, Germany, and Australia. It moves quickly, stays close to users, and concentrates on the work with the greatest impact.

The company is one of the fastest growing marketplaces. This role exists because of that growth.

Production Engineers are software engineers who join product, platform, and infrastructure teams to find and fix failures that appear at scale. They hunt for anomalies, bottlenecks, and slow degradation before anyone notices, then take each problem through to a fix and make sure the owning team keeps it fixed.

Live video and real-time commerce share the same critical path. Auctions are live and money changes hands during broadcasts, so system behavior and business results are closely linked. Latency is visible to buyers and sellers, and the most important signals are often small, concentrated in one cohort, and hidden in aggregate metrics. Spotting them early and judging which ones deserve action is central to the job.

You will embed with one team and go deep on its systems while remaining accountable for issues that fall between teams. Many of the hardest problems at this scale sit in the seams, where two services each look healthy alone, so you will hunt both within your area and across areas. You are joining early, so expect broad discovery across the platform before your embedding settles, with real influence over how Production Engineering develops here.

Responsibilities

• Work deeply with your embedded team to improve the reliability, performance, and scalability of its systems, and write the code that delivers those gains.
• Hunt for anomalies in traffic, latency, errors, and cost, both within your area and in the seams between teams, and trace each one to its root cause across services, storage, and clients.
• Link operational signals to business effects by deciding which degradations matter, for which cohorts, and which can be left alone.
• Focus on the areas with the highest risk: payments, live video, search, the bidding path, and security.
• Remove scale bottlenecks in production, then eliminate the whole class of problem rather than only the single instance.
• Get ready for peak events through capacity modeling, load testing, and failure drills.
• Strengthen observability where it is weak so future anomalies are found within minutes instead of quarters.
• Apply AI to operations, covering anomaly detection, on-call support, remediation, and reducing toil. Much of this work is new, and you will be the one to prove what works.
• Take a turn in on-call rotation with your embedded team and serve as the escalation point for live production incidents.
• Lead the response to complex failures that span teams, then drive the systemic fixes that follow.

Requirements

• A bachelor's degree in computer science or a related field, or equivalent work experience.
• 9+ years of building and debugging production services at scale. Your background may be in software engineering, production engineering, SRE, or systems engineering. Depth of experience matters more than job title.
• You think of yourself as a software engineer first, with a strong pull toward the messy side of production. You want to write code and build systems, and you notice when a graph looks slightly off and keep pursuing it.
• Solid grounding in distributed systems and systems fundamentals, including failure modes, saturation, queueing behavior, cascading failures, and how Linux, networking, and storage behave under load.
• Deep experience with observability and production debugging, plus experience in at least one of: capacity and performance engineering, load and resilience testing, incident command, or large migrations under production constraints.
• You can work effectively as an embedded engineer, entering another team's codebase, earning trust quickly, and leaving the system in better shape.
• Strong skill across languages and technologies, and comfort with cloud-native environments such as AWS or GCP, Kubernetes, and infrastructure as code. The backend is mainly Python and Elixir, with Go for performance-sensitive infrastructure. Depth and adaptability matter more to the company than familiarity with one particular stack.
• Bonus: experience with high-traffic, real-time, event-driven, or live streaming systems.

Conditions

The role offers flexibility to work from home or from one of the global office hubs, and in-person time is valued for planning, problem solving, and connection.

You must live within commuting distance of the San Francisco or New York City hub.

The posting lists 8+ years of experience as a separate requirement from the 9+ years stated in the qualifications.

Visa eligibility: US citizens or visa holders only.

The base salary range is $245K to $290K. The final figure depends on level, relevant prior experience, skills, and expertise, and the range covers base salary only, not benefits or equity.

The company is an equal opportunity employer that values diversity and does not discriminate on the basis of any protected status under applicable law.

Benefits

• Flexible time off policy along with company-wide holidays, including a spring break and a winter break.
• Health insurance options covering medical, dental, and vision.
• Support for working from home.
• Care benefits.
• Retirement plans: in the US, a 401k with Traditional and Roth options and an employer match of up to 4% of base salary; internationally, pension plans.
• A monthly allowance to use the product.
• Parental leave.