Software Engineer, Connectors Framework

We process 300+ billion rows daily, yet we operate with the intensity of a seed-stage startup. We aren't looking for "cogs in a machine." We are looking for builders., Build & Ship (70%): Implement core features like intelligent pagination, schema evolution, and rate-limiting. You'll own your code from the first line to the final deployment. Solve "Dirty" Data Problems: Real-world data is messy. You'll build self-recovery mechanisms and automated retries to keep massive pipelines running without human intervention. Learn Distributed Systems at Scale: You'll dive deep into Kafka and distributed runtimes. You won't just use these tools; you'll learn how to tune them for maximum performance. Architectural Growth: Work alongside our CTO and senior leads to understand why we make certain tech choices (e.g., Java vs. Rust) and how to design for multi-tenancy and low latency. Documentation & Quality: We believe "done" means documented. You'll write SDK docs and RFCs, ensuring our platform is easy for other developers to use., * Direct Mentorship: Work in a small, elite team with direct access to senior leadership. This is a "fast-forward" button for your career.

• AI-First Engineering: We aren't just "using" AI; we are building the infrastructure that makes AI possible for the enterprise.
• The Best of Both Worlds: The stability of a proven product with the speed and ownership of a startup.

• 2-6 years of experience in software engineering (internships count!).
• Strong Foundations: You are comfortable with Java, Kotlin, or Scala. You understand the basics of concurrency and how the JVM works.
• CS Fundamentals: You know your way around data structures, algorithms, and REST APIs.
• The "Builder" Spirit: You have a GitHub repo, a side project, or a technical blog that shows you love to tinker and learn.
• Ownership Mindset: You don't wait for a perfectly groomed ticket. You thrive in ambiguity and are willing to jump into a production issue to help the team.
• Global Collaboration Window: Ability to overlap with morning PST (Pacific Standard Time) working hours for syncs, design reviews, and collaboration with our US-based leadership and engineering teams.

Nice-to-Haves

• Exposure to the Modern Data Stack (Snowflake, Databricks, Kafka, or Spark).
• Experience with Docker or Kubernetes.
• A background in competitive programming or contributions to open-source projects.
• Interest in Generative AI and how data feeds LLM agents.

Nexla is the leading Integration platform, built with AI, for AI. Nexla takes a metadata driven approach to converge diverse integrations across Data, Documents, Agents, Applications, and APIs into a single design pattern. We accelerate the development of solutions for GenAI, Analytics, and Inter-company data. Nexla makes data users and developers up to 10x more productive by delivering a true blend of no-code, low-code, and pro-code interfaces. Leading companies including DoorDash, LinkedIn, Johnson & Johnson, and LiveRamp trust Nexla for mission-critical data. Named in the 2022, 2023, and 2024 Gartner Magic Quadrant for Data Integration Tools and top-rated by customers on Gartner Peer Insights, Nexla is a remote-first company headquartered in San Mateo, California. At Nexla, our culture is built around our core values: Have EmpathyBe Curious Be Intellectually HonestAchieve Excellence, and Remember to Relax. We put our customers at the heart of everything we do, foster a data-driven mindset, take ownership of our work, and believe in the power of teamwork to achieve ambitious goals., Why Build Your Future at Nexla? We are standing at the precipice of the GenAI revolution, but the biggest bottleneck isn't the models, it's the data. By joining Nexla, you aren't just entering a company; you are stepping into the critical layer of the modern data stack that powers the AI economy. We are the Data Fabric that enables industry titans like LinkedIn, DoorDash, and J&J to turn messy, siloed data into ready-to-use products for RAG and predictive models. This is your opportunity to move beyond simple tooling and build the actual infrastructure that democratizes data access for the next decade of innovation. If you want to solve the hardest problems in data engineering and own a piece of a market projected to hit billions, your career belongs here.