Principal Customer Engineer Jobs

Principal Product Manager - Digital Trust (Consent Management & Data Governance) — 1000 Nicollet Mall, Minneapolis,MN 55403-2542. Apply via Workday.

Principal AI GTM Programs & Transformation — 2 Locations. Apply via Workday.

Principal Machine Learning Engineer — 3 Locations. Apply via Workday.

Principal Product Manager, Marketing/Consumer Squad — 4 Locations. Apply via Workday.

Principal, Strategy and Operations — 2 Locations. Apply via Workday.

Principal Machine Learning Engineer, Agent Harness - Meta Factory — San Jose. Apply via Workday.

Principal Product Manager - Order to Cash Platform (SAP BRIM) — San Jose. Apply via Workday.

Principal Creative Higher Education Engagement Manager (UK) — London. Apply via Workday.

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: We're looking for a Principal Product Marketing Manager to help drive how Drata brings products and capabilities to market. Drata's platform spans compliance automation, enterprise GRC, TPRM, trust center, and AI governance—a growing portfolio that requires coordinated, high-quality GTM execution across every launch. This is a senior role, no direct reports, high autonomy, and high

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We’re hiring a highly influential product analytics leader who can turn ambiguous questions into sharp insight, scalable measurement, and recommendations that directly shape what we build. This person will partner closely with Product, Engineering, Design, and Growth to raise the bar on decision quality and establish a more AI-native analytics operating model. Mission Drive the product insight agenda by helping ClickUp make faster, smarter product decisions through rigorous analysis, strong product judgment, and AI-enabled analytics workflows. What You'll Do Own the product analytics agenda across product usage, activation, feature adoption, retention, and expansion, and translate open-ended business questions into structured analyses and clear recommendations Partner with Product, Engineering, and Design to define success metrics early, improve instrumentation quality, and ensure important product surfaces are measurable from launch Build reusable analysis frameworks, semantic layers, metric definitions, and self-serve resources that help product teams answer routine questions faster and more consistently Apply AI-first methods across the analytics workflow, using large language models, coding agents, and automation for tasks like query drafting, QA, validation, documentation, and first-pass synthesis while keeping human judgment at the center of final recommendations Design and interpret experiments, observational analyses, and trend investigations, including situations where data is incomplete or traditional experimentation is not feasible Surface meaningful patterns in behavioral, subscription, and

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview We’re seeking a Principal Frontend Engineer to drive the long-term technical vision for frontend engineering at ClickUp. In this role, you will lead architectural strategy across major product surfaces, solve company-wide frontend challenges, and influence how teams build and ship at scale. You will partner deeply with engineering, product, design, backend, and integrations leadership to ensure ClickUp’s frontend systems remain fast, reliable, and adaptable as the business grows. This is a hands-on technical leadership role for someone who can operate at both strategic and implementation levels, especially in a high-growth, fast-paced environment. What You’ll Do Define and drive frontend architecture strategy across product areas and platform investments Lead the design of scalable, performant systems in Angular 2+ and React that support rapid product development Solve complex cross-team technical challenges related to performance, state management, scalability, and developer productivity Partner with backend and integrations teams to shape end-to-end architecture for major features and systems Raise the bar for quality, testing, maintainability, and engineering rigor across the frontend organization Provide technical leadership on the highest-impact initiatives and unblock teams working through ambiguous or difficult problems Guide teams toward pragmatic decisions that support both speed and long-term product quality Mentor senior and staff engineers, and help shape frontend engineering culture and standards Influence roadmap and organizational decisions through strong technical judgment

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview We’re seeking a Principal Frontend Engineer to drive the long-term technical vision for frontend engineering at ClickUp. In this role, you will lead architectural strategy across major product surfaces, solve company-wide frontend challenges, and influence how teams build and ship at scale. You will partner deeply with engineering, product, design, backend, and integrations leadership to ensure ClickUp’s frontend systems remain fast, reliable, and adaptable as the business grows. This is a hands-on technical leadership role for someone who can operate at both strategic and implementation levels, especially in a high-growth, fast-paced environment. What You’ll Do Define and drive frontend architecture strategy across product areas and platform investments Lead the design of scalable, performant systems in Angular 2+ and React that support rapid product development Solve complex cross-team technical challenges related to performance, state management, scalability, and developer productivity Partner with backend and integrations teams to shape end-to-end architecture for major features and systems Raise the bar for quality, testing, maintainability, and engineering rigor across the frontend organization Provide technical leadership on the highest-impact initiatives and unblock teams working through ambiguous or difficult problems Guide teams toward pragmatic decisions that support both speed and long-term product quality Mentor senior and staff engineers, and help shape frontend engineering culture and standards Influence roadmap and organizational decisions through strong technical judgment

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

What you’ll do Act as the in-house electrical lead for Midjourney Medical: own the electrical architecture of the scanner and the technical direction for all board-level design. Own complex board design end-to-end: architecture, schematic capture, layout (high-speed digital, analog/mixed-signal, power), DFM/DFT, fabrication and assembly vendor management, bring-up, and revision control. Write firmware for embedded targets (MCU/SoC): drivers, real-time control loops, safety-relevant logic, bootloaders, and field update paths. Audit and update HDL (FPGA) code for high-throughput data acquisition, timing/synchronization, triggering, and pre-processing of ultrasound and sensor data streams. Define electrical interfaces and data contracts with software, recon/ML and mechanical teams: timing budgets, clocking/sync, signal integrity, connectors/harnessing, and failure modes. Establish electrical engineering rigor: design reviews, schematic/layout review checklists, bring-up procedures, test fixtures, and documentation suitable for a regulated medical device program (DHF, traceability, change control). Mentor and grow the electrical function; select and manage external design partners where leverage is high. What we’re looking for Deep experience designing complex boards from blank page to stable revision, including high-speed digital and analog/mixed-signal domains. Strong schematic and layout skills (Altium/KiCad or equivalent) with real signal integrity, power integrity, grounding, and EMI/EMC instincts. Solid embedded firmware background in C/C++ (and Python for tooling): peripherals, DMA, interrupts, real-time constraints, and debugging on hardware. Practical HDL experience (VHDL/Verilog/SystemVerilog) for data acquisition, timing, and streaming interfaces. Track record of owning bring-up and debug on real hardware: scopes, logic analyzers, and disciplined root-cause analysis. Technical leadership: clear trade-offs, strong written documentation, and the ability to set

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.