Senior Software Engineer, Infrastructure (Data & AI)
2 нед. назад
Южная КореяSenior
kuberneteskafkasparkflinkcloud
Build and operate infrastructure for data and AI platforms supporting high-throughput processing and real-time workloads.
О компании
- is the AI-native financial operating system for a real-time, intelligent economy. More than 676,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
- We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
- We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.
- We are looking for a Senior Software Engineer to build the infrastructure that powers our data and AI platforms.
- You will design and operate distributed systems that support high-throughput data processing, real-time workloads, and production AI applications. This includes evolving our Kubernetes and cloud foundations, improving the reliability and scalability of platforms such as Kafka, Spark, and Flink, and building infrastructure for AI traffic management and model serving.
- This is a high-impact role for an engineer who enjoys solving complex infrastructure problems, writing production software, and giving other engineering teams reliable self-service platforms. You will work across application, data, machine learning, security, and infrastructure teams to establish the technical foundations for the company’s next stage of growth.
- This role is based in Seoul, South Korea.
- Address: Units 1006, Partners Tower, 83 Gasan digital 1-ro, Geumcheon-gu, Seoul, Republic of Korea, 08589 서울 금천구 가산디지털1로 83, 1006 호(가산동, 파트너스타워)
Обязанности
- Design, build, and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms.
- Develop scalable platforms for streaming, batch processing, and real-time data workloads using technologies such as Kafka, Spark, and Flink.
- Build and evolve AI infrastructure, including AI gateways, model-routing layers, traffic management, rate limiting, authentication, observability, and usage controls.
- Develop self-service capabilities that enable data, AI, and application teams to deploy and operate workloads safely and independently.
- Partner with engineering teams to translate emerging data and AI requirements into durable platform capabilities.
- Delivered meaningful improvements to the scalability, reliability, or efficiency of our data and AI infrastructure.
- Reduced the operational effort required to deploy and manage data or AI workloads.
- Improved visibility into system performance, reliability, capacity, and cost.
- Established reusable platform capabilities adopted by engineering teams.
- Helped define the technical direction for our next generation of data and AI infrastructure.
Требования
- 5+ years in DevOps, SRE, or platform engineering, owning production systems end to end
- Strong experience designing, operating, and troubleshooting production Kubernetes environments.
- Experience building or operating distributed data infrastructure with technologies such as Kafka , Spark , or Flink OR experience developing AI infrastructure such as AI gateways or model-routing platforms.
- Hands-on experience with at least one major public cloud platform, such as AWS, Google Cloud, or Microsoft Azure .
- Strong knowledge of cloud and container networking, including DNS, load balancing, ingress, service discovery, TLS, routing, and network security.
- Proficiency in one or more of Go , Python , or Java , with experience writing maintainable production software.
- A solid understanding of distributed-systems concepts, including availability, consistency, fault tolerance, backpressure, and horizontal scalability.
- Experience operating critical infrastructure using infrastructure-as-code , automated delivery, and modern observability practices.
- Strong debugging skills and the ability to work methodically across multiple layers of a complex system.
- Clear communication skills and a track record of collaborating effectively across engineering disciplines.
- An ownership mindset: you identify important problems, drive them to resolution, and improve the underlying system rather than treating symptoms.
Другое
- Platform engineering experience, particularly building internal developer platforms or paved-road workflows used by multiple engineering teams.
- Hands-on experience with serving technologies such as SGLang, vLLM, or NVIDIA Triton Inference Server.
- Knowledge of GPU scheduling, batching, model parallelism, memory management, autoscaling, and inference-performance optimization.
- Experience improving the cost efficiency of large-scale data processing or AI inference workloads.
- Contributions to infrastructure, data-platform, Kubernetes, or AI-serving open-source projects.
- does not accept unsolicited resumes from search firms/recruiters. will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.