We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them. It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together. One Confluent. One Team. One Data Streaming Platform. About the Role: Our team sits within the Developer Productivity (DevProd) organization and is responsible for ensuring that Confluent engineers can safely and efficiently build, test, and operate our cloud at scale. As a Senior Software Engineer, you will design, build, and operate internal platform services and tools that improve developer experience and overall engineering velocity. You’ll take ownership of meaningful projects—often with some ambiguity—partnering with senior engineers and stakeholders to shape solutions, implement them, and support them in production and critical pre‑prod environments. This role is ideal for someone who: - Enjoys platform services work: multi-tenant, internal-facing services used by hundreds of engineers. - Cares deeply about testability, reliability, and developer experience in complex, distributed systems. - Thrives in R&D-leaning, somewhat ambiguous spaces where you prototype, iterate, and converge on the right solution. - Is curious about practical AI-assisted developer workflows and comfortable learning and evaluating new tools. - Is highly self-driven, naturally takes initiative, and does things that are important without being asked. What You Will Do: - Build and operate internal developer platform services — design secure, multi-tenant, and scalable services that integrate into existing DevProd systems (e.g., CI/CD, test infrastructure, developer portals), and own their reliability, performance, and monitoring. - Improve pre-production and performance testing capabilities — model realistic workloads and stress scenarios, automate performance/scale/regression tests as part of CI/CD, and provide actionable, self-service reporting that helps teams quickly see where their services break or degrade. - Explore and integrate AI-assisted workflows for developers — evaluate AI tools and frameworks, run data-driven experiments, and, where they add real value, productionize workflows such as triage assistants, anomaly detection over pre‑prod metrics, or intelligent test selection, with appropriate guardrails and visibility. - Deliver projects end to end in a collaborative way — frame problems, write clear design docs, break work into milestones, drive implementation with your peers, and participate in rollout plans that include documentation, training, and feedback loops with partner teams. - Contribute to team and engineering culture — participate in on-call and incident response for the components you own, write clear documentation, mentor junior engineers through design and code reviews, and help evolve best practices for DevProd and platform engineering. What You Will Bring: - Education & Experience – BS, MS, or PhD in Computer Science or a related field (or equivalent experience), and at least 5 years of professional software engineering experience building and operating cloud services, platforms, or large-scale distributed systems. - Technical & Platform Depth – Strong fundamentals in distributed systems and reliability; proficiency in at least one statically typed language (e.g., Java, Go) plus a scripting language (e.g., Python); experience with DevProd/DevOps tooling such as CI/CD, containers, and infrastructure-as-code. - Execution & Ownership – Demonstrated ability to independently drive projects from design through rollout, breaking work into milestones, managing risk, and delivering high-quality outcomes on time. - Collaboration & Leadership – Strong written and verbal communication skills; experience mentoring other engineers, leading design and code reviews, and influencing cross-functional stakeholders in a platform setting. - Operational Excellence – Proven track record owning services in production or critical pre‑prod environments, including on-call, incident response, and postmortems, with a strong bias towards automation to reduce toil and improve reliability. - AI Awareness – Practical experience or strong interest in integrating AI/ML or LLM-based capabilities into developer or platform workflows, along with an understanding of how to design sensible guardrails and instrumentation for safe use. You don’t need to be an AI expert, but you’re comfortable evaluating and adopting new tools. What Gives You an Edge: - Hands-on experience building or integrating AI-powered developer tools (e.g., code assistants, triage copilots, anomaly detection over logs/metrics, intelligent test selection) in production environments. - Deep experience with performance testing and benchmarking frameworks for distributed systems or multi-tenant cloud services, including workload modeling and automated quality gates. Ready to build what's next? Let’s get in motion. Come As You Are Belonging isn’t a perk here. It’s the baseline. We work across time zones and backgrounds, knowing the best ideas come from different perspectives. And we make space for everyone to lead, grow, and challenge what’s possible. We’re proud to be an equal opportunity workplace. Employment decisions are based on job-related criteria, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by law. Privacy Statement Confluent is an IBM subsidiary which has been acquired by IBM and will be integrated into the IBM organization. By proceeding with this application, you understand that Confluent will share your personal information with other IBM affiliates involved in your recruitment process, wherever these are located. More Information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here.

Before applying This role is open to contractors in accepted locations only. Please confirm your country is on the list before applying — we're unable to process applications from unlisted locations. List of accepted countries and locations. For US applicants This is a 1099 independent contractor role. It is not compatible with F-1 OPT, STEM OPT, or any visa status that requires W-2 employment, guaranteed hours, or employer sponsorship. We are unable to provide offer letters or employment verification for this role. What You'll Be Doing Help train large language models (LLMs) to write production-grade code across a wide range of programming languages: - Compare and rank multiple code snippets, explaining which is best and why - Repair and refactor AI-generated code for correctness, efficiency, and style - Inject feedback (ratings, edits, test results) into the RLHF pipeline and keep it running smoothly End result: the model learns to propose, critique, and improve code the way you do. RLHF in one line: Generate code → expert engineers rank, edit, and justify → convert that feedback into reward signals → reinforcement learning tunes the model toward code you'd actually ship. What You'll Need - 3+ years of professional software engineering experience in C++ (constraint programming experience is a bonus, but not required) - Strong code-review instincts — you can spot logic errors, performance traps, and security issues quickly - Extreme attention to detail and excellent written communication skills. Much of this role involves explaining why one approach is better than another. This cannot be overstated. - Comfortable reading documentation and language specs, and able to work well in an asynchronous, low-oversight environment Identity verification: Applicants will be required to verify their identity and confirm they have valid documentation to work as an independent contractor in their country of residence. What You Don't Need - No prior RLHF or AI training experience - No deep machine learning knowledge — if you can review and critique code clearly, we'll teach you the rest Logistics - Location: Fully remote — work from anywhere on the accepted locations list - Compensation: $30–$70/hr based on location and seniority. Note: the majority of projects run at around $30/hr — higher rates apply to senior profiles and specific project types - Hours: Minimum 15 hrs/week, up to 40+ hrs/week available — hours vary by project and are not guaranteed week to week - Engagement: 1099 independent contractor - Payment: Weekly via PayPal or Stripe ⚠️ Important: Hours are project-dependent and can vary week to week. We recommend keeping other work options open alongside this engagement rather than relying on it as your sole source of income.

• Define and own performance architecture for data path and I/O path components across distributed file systems • Lead performance analysis and optimization of large-scale, high-performance, scale-out file systems • Architect performance-aware designs across CPU, memory, storage, and network layers • Drive optimization of performance-critical file system code, primarily in C++ • Establish best practices for performance measurement, profiling, benchmarking, and regression detection • Lead deep-dive investigations into complex, system-wide performance issues • Influence system architecture with a performance-first mindset • Mentor senior and staff engineers on performance engineering techniques and methodologies • Collaborate with cross-functional teams to ensure performance goals are met across the stack • Represent performance considerations in design reviews and long-term roadmap planning

• Staff Engineers partner with Engineers, Product Managers, and Designers to solve complex, high-impact problems and deliver scalable solutions. • As a staff engineer, you shape technical direction, design systems for scale and reliability, and guide teams through sound architectural decisions. • As a Staff Engineer in the Embedded Services pillar, you will serve as the architectural lead for the Payments, Payroll and Risk solutions that drive our organization's revenue, shaping the technical strategy and long-term roadmap for some of our most critical features. • You will be a hands-on partner to our engineering teams as we tackle high-stakes scalability challenges, with a particular focus on scaling systems for peak performance and cost-efficiency. • A major part of your impact will involve guiding teams through the evolution of our ecosystem, leading the strategic migration of legacy monolithic code into modern, high-performance distributed systems. • You work across a range of technologies, helping evolve our stack and evaluate new approaches. • This is an individual contributor role with no direct people management responsibilities, relying on influence, technical leadership, and cross-team alignment to drive impact.