Senior Principal Engineer, AI & Business Transformation

Job description

Who is Forcepoint? Forcepoint simplifies security for global businesses and governments. Forcepoint’s all-in-one, truly cloud-native platform makes it easy to adopt Zero Trust and prevent the theft or loss of sensitive data and intellectual property no matter where people are working. 20+ years in business. 2.7k employees. 150 countries. 11k+ customers. 300+ patents. If our mission excites you, you’re in the right place; we want you to bring your own energy to help us create a safer world. All we’re missing is you! Forcepoint's operating model hasn't kept pace with the business — accumulated approval layers, fragmented process ownership, and substantial AI-driven efficiency left unrealized. The AI & Business Transformation function exists to close that gap through a continuous loop: sense where the business is costing money or slowing down, redesign those processes end-to-end, and deliver them as AI-driven workflows on the Forcepoint Intelligence Platform. The Senior Principal Engineer sits at the intersection of business intent and engineered outcome. Day-to-day, that means partnering closely with the VP to sequence and deliver the transformation portfolio; co-architecting the agentic delivery layer with the CIO and platform engineering team; aligning on data foundations and benefits realization with the CFO and Finance; coordinating workforce impact and AI Ambassador adoption with the CHRO; ensuring security, governance, and auditability with the CISO; and working directly with functional and business-unit leaders who own the processes targeted for transformation. This role is the most senior technical authority in this function — an individual-contributor reporting to the VP, AI & Business Transformation, with no direct reports and enterprise-wide scope. Influence is exercised through architecture, invention, and technical judgment. This person sets the technical vision across all three pillars of the loop: the data foundation that enables sensing, the process architecture that guides redesign, and the agentic systems and tooling that deliver transformation at scale. The platform foundation is already in place — the Forcepoint Intelligence Platform is live, with MCP connectors to core business systems, a growing library of production agents, and AI Ambassadors embedded across every function. The transformation portfolio covers high-value flows including customer deprovisioning, renewal forecasting, quote-to-cash, lead-to-opportunity, and SKU creation. What's missing is the senior technical authority to make the whole loop compound: turning point solutions into a coherent, reusable agentic system that gets faster and smarter with every flow it redesigns. Key Responsibilities 1. Architecture & Technical Vision Set the cross-pillar technical vision. Own the end-to-end architectural vision that connects sensing, redesign, and delivery into a single compounding loop — ensuring the data foundation, process designs, and agentic systems reinforce one another rather than fragmenting into disconnected point solutions. Architect the agentic delivery layer. Define how redesigned processes become production-grade AI agents, Skills, and tooling on the Forcepoint Intelligence Platform — establishing the reference architecture, orchestration patterns, exception-handling models, and human-in-the-loop standards the broader organization builds against. Build AI-first capability on AWS and Bedrock. Establish the cloud and model foundation on AWS and Amazon Bedrock — delivering model access, agent orchestration, and platform services that are scalable, observable, and cost-efficient, while keeping the architecture model-flexible enough to adopt the strongest models as the landscape evolves. 2. Process Redesign & Delivery Translate process redesign into engineered outcomes. Partner with functional leaders and transformation owners to take flagged, re-architected flows and turn them into automated, governed, observable systems — owning the technical design from contract-end trigger through cross-system orchestration to benefits realization. Prove value through visible wins. Identify and deliver high-leverage quick wins that build organizational confidence, then convert them into durable, scalable architecture — balancing near-term proof with long-term platform coherence. 3. Data, Measurement & Governance Strengthen the sensing foundation. Shape the data architecture, KPI instrumentation, and benefits-realization tracking that let the organization measure whether redesigned work actually moved a number — reconciled with Finance and built on the enterprise data platform. Drive technical governance for AI. Partner with platform, security, and legal stakeholders to define how AI is applied responsibly across elevated flows — covering model selection, data handling, auditability, and the governance thresholds that keep enterprise-scale automation safe and compliant. 4. Standards, Patterns & Organizational Capability Establish reusable standards and patterns. Create the frameworks, accelerators, and engineering operating mechanisms that make each successive flow faster to deliver than the last, raising the bar for quality, reliability, and velocity across the transformation portfolio. Act as a force multiplier. Mentor engineers, AI Ambassadors, and functional teams; codify best practices; and elevate the collective technical capability of the organization — multiplying impact through influence and invention rather than direct headcount. 5. How You'll Work This role is intentionally high-leverage, not high-headcount. The Senior Principal Engineer operates as an individual contributor with enterprise-wide technical authority and a mandate that extends across every function in the transformation portfolio. Work through functional leaders, transformation owners, and embedded engineering teams — aligning and accelerating execution through technical credibility and demonstrable results. Partner closely with the VP, AI & Business Transformation, Leadership Team, and the CIO to drive technical priorities across the enterprise. Build reusable architecture and engineering patterns that compound across regions, functions, and future transformation initiatives. Act as a technical mentor and force multiplier — building the AI-first engineering capability of the organization through standards, coaching, and hands-on example. Foster a culture of accountability, continuous improvement, and outcome-based engineering execution. Required Qualifications 15+ years in software engineering, architecture, or platform development, with a sustained track record of operating at the most senior technical levels (Principal, Distinguished Engineer, Fellow, or equivalent) and influencing outcomes across an enterprise rather than a single team. Demonstrated mastery of enterprise, application, and data architecture — including designing systems that span multiple business domains, integrate disparate platforms, and operate reliably at scale. Deep, hands-on expertise in AI-first and agentic engineering — designing and delivering production systems built around LLMs, agents, and orchestrated tooling, not merely experimenting with them. Proven ability to move agentic work from proof-of-concept to dependable, governed production. Proven experience translating complex, cross-functional business processes into engineered systems — re-architecting end-to-end flows and the data, integration, and automation that make them run. Deep, hands-on command of AWS — including Amazon Bedrock for model access and agentic delivery — and modern platform engineering: scalability, performance, observability, and cost optimization at enterprise scale. A history of measurable business impact: compressed delivery cycles, material cost reduction, productivity multipliers, or revenue enablement attributable to technical leadership. Exceptional ability to influence without authority — aligning functional leaders and engineering