As Director of Engineering for Operations & AI Automation, you'll own the engine room of the Magnit Global VMS platform, the systems that power clients, suppliers and workers with intelligent workflows, and the data layer underneath. You'll lead 3–4 teams building agentic capabilities, automation, and insights that turn manual operational work into product. You'll set technical direction, raise the engineering bar, and partner closely with Product, Operations to ship outcomes that customers feel.

This is both hands-on-the-keyboard, hands-on-the-strategy role for a leader who has shipped real AI into production, not slideware, and who knows the difference between a demo and a system that large number of enterprise users depend on at 9am Monday.

What you'll do

• Lead the org. Manage and grow 3–4 engineering teams across the product line. Hire, coach, and develop managers and senior ICs.
• Set technical direction. Own architecture, delivery priorities, and engineering standards across your teams. Make the trade-offs that matter, build vs. buy, speed vs. reliability, automation vs. headcount.
• Build with AI, not around it. Ship production-grade AI agents, RAG systems, workflow orchestration, and tool-calling capabilities. Drive measurable reduction in manual work and meaningful lift in operational accuracy.
• Turn operations into product. Partner with Product, Operations to convert recurring operational pain into reusable platform capabilities, anomaly detection, intelligent reporting, decision support, automated workflows.
• Raise the engineering bar. Drive excellence across architecture, code quality, testing, CI/CD, observability, security, and release management. Improve delivery predictability and platform reliability quarter over quarter.
• Use data as a product asset. Mine platform data for risk signals, efficiency gaps, and product opportunities. Make data-driven prioritization the default, not the exception.
• Plan capacity, ruthlessly. Balance roadmap delivery, automation investment, technical debt paydown, and innovation across teams. Defend the long-term while shipping the quarter.
• Build the culture. Establish clear ownership, high standards, and a high-performance, low-drama team culture. Develop the next layer of engineering leaders under you.

What you'll bring

• 10+ years of engineering experience, including 5+ years leading engineering teams (managers reporting to you is a plus).
• Track record of leading teams that built and scaled enterprise SaaS platforms, VMS, workforce management, procurement, FinOps, HR Tech, or workflow automation.
• Practical, production experience with AI agents, GenAI, RAG, agent orchestration, tool-calling, and AI evaluation. You've shipped this in front of real users, not just prototyped it.
• Strong fluency in cloud platforms (AWS), microservices, APIs, event-driven systems, DevOps, and observability.
• Demonstrated ability to improve engineering quality, delivery predictability, platform stability, and team performance and the metrics to prove it.
• Strong product mindset. You connect technology decisions to customer value and business outcomes, and you push back when the math doesn't work.
• A track record of hiring, developing, and retaining strong engineering talent, including managers.

Nice to have

• Domain depth in worker engagement, vendor/staffing operations, or enterprise workflow automation.
• Experience shipping analytics, dashboards, anomaly detection, recommendation engines, or conversational insights at scale.
• Experience operating global, multi-region platforms across diverse customer segments.