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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer, Data Products - **Company:** Shipps Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $100,000.0 - $287,000.0 - **Contract:** Permanent contract - **Skills:** Reference Implementation, Application Programming Interfaces (APIs), Artificial Intelligence, Applications Architecture, Application Services, Information Engineering, Data Infrastructure, Data Systems, Software Design Documents, Software Engineering, Autoscaling, Build Management, Kubernetes, Machine Learning Operations, Databricks - **Published:** September 19, 2026 - **Apply:** https://www.builtincolorado.com/job/principal-software-engineer-data-products/11261930?handler=ApplyRedirect ## About the Role * 10+ years of software engineering, with deep ownership of large-scale production systems. You have set the engineering standard on a team, not just met it. * Track record as a principal-level individual contributor. You set technical direction across teams, wrote the RFCs, ran the design reviews, and delivered multi-quarter roadmaps without direct authority. * Depth in distributed, data-intensive production systems. You have made design decisions driven by latency, throughput, availability, and cost, and you have experience operating them in production. * Deep Kubernetes expertise: experience building and deploying containerized production services, with the ability to navigate autoscaling, resource constraints, and resilience patterns to define deployment standards for ML workloads. * Strong working experience alongside data scientists and data engineers. You have taken analytical or prototype work and made it production grade. * Proven adoption and mentorship. Teams chose the standards and tooling you built because they were better, not because someone mandated them, and engineers got better from working with you. Bonus * Solid understanding of what a good ML development workflow looks like, enough to advise a team building one. * Experience building agentic AI solutions for customers, including evaluation harnesses, guardrails, and observability. * Hands-on Databricks, specifically with ML tooling. * Feature store patterns and online-offline consistency. ## Description That only works if the systems behind it are built well and run smoothly. We are looking for a principal engineer to set the standard for how we design, review, build, and operate those systems. You will work alongside our software engineers, data scientists, and data engineers to turn analytical and prototype work into the data-intensive systems, integrated with AI and ML, that our customers depend on for logistics decisions at scale., * Set the bar in design review and code review by demonstrating it. * Raise the standard for testing, observability, and operational readiness across the Data org. * Turn repeated solutions into reusable primitives. Document them so the next team does not need you. * Grow the next set of technical leaders. Pair, mentor, and hand off ownership. Architecture across engineering, data science, and data platform * Design and build the interfaces where Shippo's application services meet our ML and data systems. Write the reference implementation, not only the design doc. * Author technical RFCs to guide data, API, and application architecture. Run the reviews that make those decisions hold. * Set the performance, security and reliability standards for how application services call data and ML systems. Data to production * Ensure analytical and data engineering work turn into systems that meet our bar for security, quality, maintainability, and performance. * Pragmatic approach working directly with data scientists and data engineers to find the friction in their workflow, then remove it. * Ensure our data products deliver customer and business impact. Balance speed to market against architecture, and say which one wins and why. AI and ML * Advise on the development workflow from experimentation to production: train, track, register, validate, deploy, monitor, retrain. * Experience building agentic workflows. Prove them in production against real traffic with real evaluation. Harden the ones that deliver value and kill the ones that do not. ## Related Videos - [Fifty Shades of Kubernetes Autoscaling](https://www.wearedevelopers.com/videos/813-fifty-shades-of-kubernetes-autoscaling) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Serverless-Native Java with Quarkus](https://www.wearedevelopers.com/videos/243-serverless-native-java-with-quarkus) ## Related Articles - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)