Senior Vice President, Engineering

Overview 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. We are 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. Location: Hybrid role with regular onsite workdays in our San Jose, CA corporate office. Reporting to: Chief AI Development Officer. Responsibilities 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 optimizing latency and cost across hosted and self-managed models. People, Culture & Talent Recruiting, developing, and retaining top-tier engineering leaders; building 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; representing engineering at the Board and with strategic customers as needed. Converting customer feedback into engineering priorities; ensuring 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; ensuring 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; owning integration plans across systems, data, security, and people—aligning product and architecture roadmaps post-close. Qualifications 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 with strong governance, telemetry, and quality gates—building around AI, not just integrating it. Deep expertise scaling cloud systems (multi‑tenant, high-throughput) on AWS/Azure/GCP; strong instincts for bottlenecks and performance engineering. Proven ownership of reliability and security at scale: SRE practices, SLOs/SLIs/Error Budgets, secure SDLC, vulnerability management, incident response, and postmortems. Track record of portfolio execution with short release cycles, outcome-based planning, and products with demonstrated customer adoption. Mastery of modern engineering: Kubernetes, Docker, microservices, Java and/or polyglot stacks, event streaming, and cloud-native data systems. Hands‑on fluency with the AI/ML stack: Python, PyTorch/TensorFlow, vector DBs, feature stores, LangChain/Semantic Kernel, MLflow/KServe, and model evaluation and observability. Strong executive presence: able to influence at CEO/Board level and inspire large, distributed teams with clarity and conviction. Key competencies: strategic vision & enterprise thinking; executive influence & stakeholder leadership; organizational leadership & talent development; decision-making & operational judgment; customer-centric mindset & business acumen. Compensation & Benefits Base salary range: $350,000 – $375,000 a year. Eligible for an executive bonus plan, equity, and a full range of medical and other benefits. Flexible work schedule / remote roles. Unlimited personal time off. 12 holidays off per year. 4 days volunteer time off per year. Eligible for 4 company achievement days off per year. Variety of health care and well-being benefits. Paid family/parental leave. Equal Opportunity Employer Automation Anywhere is an affirmative action and equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis. #J-18808-Ljbffr