Infrastructure Backend Developer

WSC Sports, the pioneer in AI-powered sports content technology, empowers their clients world-wide to connect with their fans through AI-tailored sports content experiences. WSC Sports’ platform automates the creation, management and distribution of content, enabling sports rights holders to expand reach, grow fan bases, and unlock revenue opportunities across digital platforms.

Why WSC Sports:

You’ll work in an awesome environment alongside some of the most innovative people in the industry, using cutting-edge technologies and tools (video editing, Gen AI, data, etc.). At WSC Sports, you have the opportunity to directly influence the products and tools used by our clients, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN - and that’s just the beginning of what WSC Sports has to offer! Join us and be a part of the best team in tech as we Fuel the Fandom worldwide.

We are seeking an Infrastructure Backend Developer to join a backend-only engineering team that owns some of the company's highest-scale and most business-critical services - the backbone of our product. The team is responsible for video ingestion of HLS streams, a video editing service that runs on CPU and GPU workloads in Kubernetes, and 20+ additional backend services. Our infrastructure runs 24/7 with elastic scaling that can grow to very high capacity during peak usage.

In this role, you will own outcomes end-to-end, mentor teammates, and drive both technical design and code reviews. You should be a methodical problem-solver capable of decomposing complex initiatives and prioritizing effectively. Above all, we value high-ownership, low-ego collaborators who bring positive energy to the team.

What you’ll do:

Design, build, and operate backend services and APIs at scale, with emphasis on reliability, performance, cost awareness, and operability in production.
Own projects end to end: clarify requirements with stakeholders, propose approaches, implement incrementally, and follow through on rollout, monitoring, and iteration.
Collaborate with Product, Operations, Account, DevOps, and engineering teams to deliver cohesive solutions for streaming ingestion, processing pipelines, and backend infrastructure.
Optimize systems for throughput, latency, resource utilization, and stability under spiky and peak traffic patterns.
Investigate and resolve production issues with a calm, systematic approach; improve observability and runbooks so incidents become easier to prevent and recover from.
Mentor engineers through pairing, design discussion, and feedback; setting standards and raising the bar.
Participate actively in agile planning, architectural conversations, and code reviews; contribute to technical review and sound engineering judgment across the team.
Stay current on relevant technologies (cloud, Kubernetes, streaming, data stores, performance engineering) and pragmatically adopt tools - including AI-assisted development where they improve velocity without compromising quality or stability.

Requirements:

Bachelor's degree in Computer Science, Software Engineering, or a related field - or equivalent depth of experience.
Minimum of 5 years of professional experience building and operating backend systems in SaaS / cloud environments.
Strong proficiency in at least one mainstream backend language (e.g. Java, Python, C#, or similar), with the ability to ramp on our stack.
Solid understanding of distributed systems, microservices, and cloud concepts; hands-on experience with Kubernetes (workloads, scaling, deployments) is a strong plus.
Experience with SQL, schema design, and performance-minded querying.
Comfort with Git, CI/CD, and agile delivery; ownership of features from design through production.
Demonstrated ability to lead technical initiatives, coordinate across roles, and communicate clearly to both engineers and non-engineering partners.
Evidence of mentorship or technical leadership (formal or informal): helping others grow, reviewing designs, and improving team practices.
Pragmatic use of AI development tools (e.g. Cursor, Claude, or similar) as part of a disciplined engineering workflow.
Excellent problem-solving, prioritization, and multitasking in a fast-paced environment - without sacrificing clarity or follow-through.

Bonus Points:

Experience with video pipelines, HLS / streaming ingestion, transcoding or video related tools such as FFmpeg, FFprobe, MediaInfo, etc.
Azure (or comparable hyperscaler) at scale, including networking, identity, and cost/performance tradeoffs.
.NET Core or other frameworks used in large service estates.
Background in high-throughput APIs, async processing, or large batch workloads.

Work Model:
Hybrid