AI Engineer and Data Systems Architect
at Nudge Security · 11-50 employees
- Employment
- Full Time
- Location
- North America
- Posted
- 5d ago
at Nudge Security · 11-50 employees
Nudge Security provides automated SaaS and AI security governance at the workforce edge, giving organizations real-time visibility and policy-driven guardrails for employee-chosen applications.
AI ENGINEER & DATA SYSTEMS ARCHITECT ABOUT NUDGE SECURITY Nudge Security delivers AI and SaaS security governance at the Workforce Edge, where employees make thousands of technology decisions every day. Our automated, policy-driven guardrails reach employees when and where they work, enabling rapid technology adoption while minimizing risk and sprawl. Through unrivaled discovery capabilities, AI-driven risk insights, and behavioral science-based engagement, we make security a natural part of how modern work gets done rather than an obstacle to innovation. Nudge Security was founded in 2021 by Russell Spitler and Jaime Blasco and is backed by Ballistic Ventures, Forgepoint Capital, Cerberus Ventures, and Squadra Ventures. We're looking for an exceptional AI Engineer & Data Systems Architect who thrives in high-growth environments, loves building new business, and is excited to help shape one of cybersecurity's fastest-growing categories. SUMMARY Most companies bolt AI onto the way they already work. We'd rather build the way we workaround it. Reporting to our VP of Engineering, you'll own how AI is used across Nudge Security: the rollout, the enablement, the agents, and the orchestration of the business systems those agents run on. Treat this as a product, because it is one. You'll have users, a roadmap, telemetry, release discipline, and a bar for quality every bit as high as the one we hold for what we sell to the market. As we scale, the accuracy and efficacy of our business operations depend on the system and data architecture you build and run. That's real weight, and it comes with real latitude to decide how the work gets done. Very few companies combine that scope, the data flowing through it, and the authority to change it in one role, and fewer still have a leadership team that already believes AI belongs at the center of how a company operates rather than at the edges. We help our customers govern AI adoption, so we understand this problem from the inside. You'll work at the front edge of operational AI, with the access, the budget, and the air cover to find out what it can actually do. WHAT YOU’LL OWN Systems integration, automation, and AI implementation - Own how our go-to-market and customer-facing platforms connect to each other and to the rest of our data. Integrations, sync logic, data flow, automation, and the AI capabilities we build on top of them. - Partner closely with the people and teams who administer each platform day to day. They own their configuration and process; you're the technical counterpart who owns the data and system architecture to ensure it can deliver what they need, and who advises on object and lifecycle modeling where it affects data moving between systems. - Manage the SaaS integration surface: what's connected to what, which scopes are granted, and who has access. - Contribute the integration, data, and AI-readiness assessment when we evaluate, onboard, or retire tools, working alongside system owners, security, and finance. Data pipelines and analytics - Own the flow of product, web, and customer data from our event pipeline into the warehouse and out to the product analytics, BI, and go-to-market tools that depend on it. - Partner with product and engineering on in-product instrumentation: define and maintain the tracking plan, review event schemas before they ship, and catch breakage before a dashboard does. - Partner with GTM Ops on data flows and instrumentation across the GTM tech stack and data warehouse to support GTM operations and reporting needs. - Own and maintain the SQL and data models that turn raw events into the metrics the business actually uses. Reporting and forecasting - Build and maintain reporting across the funnel — pipeline, conversion, activation, retention, and revenue — so that each team has a view they trust. - Own revenue and forecast reporting in our financial planning platform, and reconcile it against CRM and product data so the numbers tie out. - Support executive and board reporting cycles. AI enablement - Help teams across the company adopt AI assistants and the AI features embedded in our tooling — safely and usefully, not as a novelty, but as a way to remove real work. - Build the automations and internal workflows that let a small systems function support a growing company. - Establish sensible guardrails with security around what data goes where. Security and compliance - Manage the SaaS integration surface: what’s connected to what, which scopes are granted, and who has access. - Work with the security team to ensure every integration, data flow, and access grant conforms to our compliance obligations. - Treat data minimization and least privilege as defaults, not afterthoughts. - Document data flows well enough to survive an audit. WHAT WE’RE LOOKING FOR - 5+ years in business systems, revenue operations, analytics engineering, or a similar role — ideally at a B2B SaaS company. - Strong SQL. You’re comfortable in a cloud data warehouse, can model data and debug a pipeline, and know where the line is between “I’ll fix this” and “this needs an engineer.” - Practical experience with a CDP or event pipeline (Segment, RudderStack, or similar) and a product analytics tool (Mixpanel, Amplitude, or similar). - A track record of building reporting that people actually use, and of getting different systems to agree on the same number. - Genuine fluency with AI tooling — you’ve used it to automate real work, not just to draft emails. - Comfort operating in a security-conscious environment, and good instincts about data handling and access. - Strong written communication. Much of this job is translating between technical systems and the people who depend on them. NICE TO HAVE - Experience owning a financial planning and forecasting platform, and reconciling it against CRM and product data. - dbt or similar transformation tooling. -