Senior Vice President, Engineering

About the role

Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry's first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics-all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential. Our opportunity: We're seeking an SVP of Engineering to lead our global engineering organization at a defining moment in the convergence of Automation and AI. You will own end-to-end engineering strategy and execution, driving the vision for AI-native offerings at scale, from foundational architecture to AI-powered product delivery. Partnering closely with Product, Design, Data, and GTM leaders, you'll embed intelligence across our full platform, enabling enterprises to build, automate, and operate smarter. You're a deeply technical, hands-on executive with a proven track record of shipping AI-native products at scale, elevating engineering craftsmanship, and turning ambitious AI bets into measurable business outcomes. This is a pivotal moment in Automation and AI, and you'll shape how we lead it. Who you'll report to: This role will report to our Chief AI Development Officer Location: Hybrid role with regular onsite workdays in our San Jose, CA corporate office You will make an impact by being responsible for: Strategy & Organizational Leadership Setting the engineering vision and multi-year roadmap aligned to company strategy; translating business goals into clear technical outcomes and AI-driven portfolio priorities Leading and scaling a multidisciplinary org (Apps, Platform, AI/ML) with VP/Director leaders and 100+ engineers across geographies Establishing architecture guardrails and clear standards for quality, security, privacy, and reliability-with AI governance built in from the ground up Partnering with Product & Design on outcome-based roadmaps and customer value hypotheses; shaping pricing and packaging strategy for AI-native features with PM & Finance Technical & Operational Excellence Owning SDLC and delivery excellence-predictable releases, high change success rate, and reduced cycle time through robust CI/CD, automation, and trunk-based development at scale Driving reliability and performance (SLOs/SLIs/Error Budgets, 99.9x+ availability), capacity planning, and cloud cost efficiency through rigorous FinOps and unit economics discipline AI-Native Product Leadership Partnering with Product and Data Science to define and ship AI-native capabilities: intelligent agents, automation co-pilots, autonomous workflow orchestration, RAG pipelines, and safety-by-design governance Building and scaling ML/LLM platform foundations-feature stores, vector databases, prompt and model management, evals, red teaming, and monitoring for drift, toxicity, and PII leakage Establishing model lifecycle and compliance practices (data provenance, auditability, bias testing, human-in-the-loop review) and optimize latency and cost across hosted and self-managed models People, Culture & Talent Recruiting, developing, and retaining top-tier engineering leaders; build an inclusive, high-accountability culture that celebrates craftsmanship, AI innovation, and sustainable pace Implementing succession planning, leadership pipelines, and clear career ladders; raising the bar through calibration, mentoring, and principled performance management Being a visible technical voice-internally (all-hands, engineering demos) and externally (conferences, customer briefings, analyst interactions) Stakeholder, Customer & Board Engagement Serving as a trusted executive partner to Product, Sales, Customer Success, and Support; represent engineering at the Board and with strategic customers as needed Converting customer feedback into engineering priorities; ensure compliance, data residency, and enterprise-grade requirements are built into the roadmap Financial & Vendor Stewardship Owning engineering budgets, vendor strategy, and build-vs-buy decisions; ensure efficient spend across cloud, data/ML infrastructure, and tooling with measurable ROI Leading risk management (operational, technical, privacy), quarterly business reviews, and executive reporting with clear KPIs M&A & Integration Leading technical diligence for acquisitions; own integration plans across systems, data, security, and people-aligning product and architecture roadmaps post-close You will be a great fit if you have: Bachelor's degree in Engineering, Computer Science, or a related technical field (Master's degree a plus) 15+ years in software engineering; 7+ years leading large-scale, multi-team organizations at VP/SVP level in enterprise SaaS Demonstrated success shipping AI-native products in production

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