Technical Lead Manager

### About Nexla 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, headquartered in San Mateo, California. At Nexla, our culture is built around our core values: **Have Empathy**, **Be Curious**, **Be Intellectually Honest**, **Achieve 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. **Nexla, briefly** Nexla is the data layer for enterprise AI. We give AI apps and agents the connectivity, context, and governance to work across more than 1,000 enterprise systems in real time, and we process over a trillion records a month doing it. DoorDash, LinkedIn, Johnson & Johnson, Instacart, and LiveRamp run mission-critical data on us. Honorable Mention in the Gartner Magic Quadrant™ for Data Integration Tools, and top-rated by customers on Gartner Peer Insights four years running. Founded 2016, remote-first, headquartered in San Mateo. Our values are short and we actually use them: Have Empathy. Be Curious. Be Intellectually Honest. Achieve Excellence. Remember to Relax. **Role, briefly** Nexla’s connector layer is what talks to everything else: over a thousand SaaS applications, databases, streams, files, and APIs, bidirectionally, each with its own schema quirks, auth scheme, rate limits, and retry semantics. You would be the most senior engineer on it, and the person four to six engineers report to, working alongside our backend, API, and UI teams. The split is roughly 80% hands-on design and code, 20% growing the team. If you are looking to step off the keyboard, this is the wrong job. **What you’ll own** - The architecture of the connector layer. You make the calls on how we abstract a thousand systems and handle formats like JSON, Parquet, and Avro at high throughput, and you write the hard parts yourself. - The connector roadmap. You decide what ships, what gets deprecated, and in what order, working directly with product, customer success, and support on what customers actually need. - Reliability of what your team ships, on-call included. Fewer failures reaching customers, and better tooling so the team sees problems before customers do. - The four to six engineers around you. Hiring, growth, and raising the technical bar, mostly through design review and pairing. Formal management runs to about a day a week. *Ninety days in: you have shipped something non-trivial to production, named the two worst parts of the current design with a proposal attached, and the team has started routing hard design questions to you before they route them upward.***A real problem you’d hit here**We have thousands of connectors, with thousands of customer pipelines running on them. Each one has to scale in two directions at once: the volume of data moving through it, and its reliability under that volume. This is not a problem you solve and close. The connector surface keeps growing, so holding both properties is a constantly evolving task, and it is the standing problem of this team. **Must-haves** - 10+ years building backend systems, and you are still hands-on. You can point at code you wrote recently and are proud of. - Deep JVM experience. You have debugged distributed systems where the failure was not in the code you wrote. - Production depth in Kafka, Redis or Memcached, and APIs over gRPC and REST, Kubernetes at high throughput. - You have led engineers technically: design review, mentoring, raising the bar on a team. Formal people-management experience is welcome but not required. - You use AI tools in your actual work and can say specifically where they help and where they mislead you. **Bonus points** - Data integration, ETL, or iPaaS background. - You have wrangled JSON, Parquet, Avro, and worse at scale. - You have carried direct reports before, including performance conversations. **You’ll thrive here if** - Urgency is your default. You'd rather ship a good answer this week than a perfect one next quarter, and you make that call without being asked. - You own the outcome, not your slice of it. When something breaks between two teams, you fix it rather than route it. - You close loops. What you pick up gets finished, and the people around you stop having to follow up. - You set the pace. Four to six engineers will calibrate their urgency to yours, and you know that. - You want the design authority that comes with the title without giving up the keyboard. *One thing to be clear about: this role grows through technical depth and scope, not through headcount. The 80/20 split is deliberate and will stay that way* **How we hire -** Five conversations, about one to two weeks end to end. - **Exploratory call with our CTO.**A real conversation about the problem space and whether this scope is what you actually want. 45 min. - **Design and architecture.** How you shape systems, on problems close to what we run in production. 60 min. - **Distributed systems design.** Throughput, failure modes, and the tradeoffs you would defend under pressure. 60 min. - **Coding.** Working through real code rather than a puzzle. 60 min. - **Leadership conversation with a co-founder.** Ownership, judgment, and how you raise the bar of the people around you. 45 min. ***On AI in the coding round.*** *Use it the way you would on the job, ours or anyone else’s. We build AI tooling and we expect you to use AI tooling, so watching you work without it would tell us nothing useful. What we dig into is your judgment: what you delegated, what you verified, and what you threw away.* *You will hear from us either way.***The practical stuff** Bengaluru, hybrid. Compensation includes base salary, bonus, and equity, set by depth and experience rather than by title. You will work closely with our US leadership team, so some overlap with Pacific hours is part of the job. We will be specific about how much in the first conversation rather than springing it on you later. **Worth a look before you apply:** - What we are building now. [MCP Studio](https://nexla.com/mcp-studio/) and [Express](https://nexla.com/express/), our two newest bets. - Who uses us, and why. [](https://nexla.com/customers/) - The product in engineer terms. [](https://docs.nexla.com/) - Our CEO on why we take "Remember to Relax" seriously. [Read the founder story](https://nexla.com/what-we-value-at-nexla/) - Everything else. [](https://nexla.com/) · [Blog](https://nexla.com/blog/) · [All open roles](https://nexla.com/jobs/) **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.