Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
API
AWS @ 4
Algorithms
Azure @ 4
Distributed Systems @ 7
GCP @ 4
Go @ 6
Java @ 6
LLM @ 6
Machine Learning @ 6
Networking @ 7
Observability
Scala @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Confluent is building a data streaming platform that enables companies to process information in near real time. The AI team develops capabilities that allow customers to run machine learning models and AI agents directly on streaming data without moving it to external technology stacks.
About the Team
The team owns its products end to end, from user-facing APIs through the production inference serving layer. It works closely with platform teams and operates in a high-ownership, high-autonomy environment focused on scalable AI infrastructure.
Responsibilities
- Design, develop, and operate large-scale, high-performance infrastructure powering Confluent Cloud.
- Build foundational software that improves reliability, scalability, and efficiency across cloud environments.
- Solve distributed systems problems involving consensus algorithms, failover strategies, and resource allocation.
- Collaborate with teams across Confluent to optimize infrastructure for real-time data streaming use cases.
- Troubleshoot and improve system reliability, observability, and performance across AWS, Azure, and GCP.
- Architect scalable and cost-efficient serving layers that enable customers to run inference and AI agents directly on streaming data.
Requirements
- 2–5 years of industry experience designing, building, and supporting backend systems in production.
- Strong fundamentals in distributed systems, cloud infrastructure, and networking.
- Experience building and operating large-scale, highly available systems.
- Understanding of cloud platforms such as AWS, Azure, or GCP and their services.
- Proficiency in Java, Scala, C++, Go, or another statically typed language.
- Strong problem-solving skills and the ability to work as a self-starter in a fast-paced environment.
- BS, MS, or PhD in computer science or a related field, or equivalent work experience.
Preferred Qualifications
- Exposure to model serving, LLM or agent infrastructure, or streaming data systems.
- A background in machine learning research or model training is not required; the role focuses on building and operating a reliable AI-serving platform at scale.
Company Information
Confluent is an equal opportunity workplace. Employment decisions are based on job-related criteria without regard to protected characteristics. Confluent is an IBM subsidiary that has been acquired by IBM and will be integrated into the IBM organization.