Artificial Intelligence & Data Vice President
New Today
As the global standard for process intelligence and automation, were trusted by over 10,000 public and private sector organizations across 90 countries. Our customers, from industry giants like Amazon, Coca-Cola, and Microsoft, rely on the Nintex Platform to accelerate their digital transformation journeys by managing, automating, and optimizing business processes quickly and efficiently. Working at Nintex as an engineer means building more than just software; We are seeking a highly strategic and execution-oriented Vice President of Engineering to lead our next chapter of innovation in artificial intelligence, data-driven platforms and process intelligence. This executive will own the technical direction, architecture, and delivery of our AI and data engineering capabilities, as well as modernizing our process intelligence products to ensure our platform is intelligent, scalable, and enterprise ready.
You will lead high-performing engineering teams across three strategic priorities partnering closely with product, platform and go-to-market leaders:
Advancing our AI engineering capabilities driving the development of common AI frameworks, multi-agent architecture, AI infrastructure & governance, model selection & training and context engineering that accelerates AI capabilities for customer to build, operate, manage and optimize automation solutions on the Nintex platform
Modernizing and differentiating our process intelligence capabilities that help customers identify, govern and optimize processes across their organization
Building a centralized data intelligence platform that serves as the single source of truth for customer analytics, internal business intelligence, and AI needs across all products.
This role offers a unique opportunity to own a growing vertical SaaS product as well as strategic platform capabilities to shape the Nintex vision through execution.
Set the vision, define and execute a comprehensive engineering roadmap aligned with business strategy
Collaborate closely with Product, Data Science, and Platform teams to evangelize development & adoption to accelerate platform strategy
buy, open-source, technical debt, data governance, and investment priorities.
Represent our Process Management, Data and AI strategy to executive stakeholders, customers, partners, and industry as needed.
Build & own common AI frameworks, AI platform and infrastructure components and multi agent architecture, RAG patterns, orchestration & governance patterns across the platform
Create systems to leverage and experiment with best of breed AI innovation in the industry balancing performance, cost and quality tradeoffs
Evolve process intelligence capabilities using modern cloud native multi-tenant technology to unlock superior customer experience, development velocity & operational efficiency
Lead design and implementation a unified data platform from ingestion, processing through transformation pipelines leveraging Databricks Delta Lake
Drive adoption of modern data stack for core platform, orchestration, streaming, data quality, metadata management, monitoring and governance
Ensure platform scalability, reliability, and performance to support rapidly growing usage while solving for ease of adoption by customer & internal teams
Recruit, grow, and lead exceptional engineering talent across AI and data engineering
Build urgency to move fast while balancing engineering excellence, scalability and security
Launch agentic AI build experience for full scale process automation solutions leveraging 5+ product domains
Establish AI best practices to accelerate 20+ runtime AI capabilities across the platform
Evolve platform intelligence capabilities to a modern cloud native system seamlessly integrated within the Nintex Automation Platform
Successfully migrate 5+ major products to the unified data platform
9% platform uptime with best-in-class data latency SLAs
Enable 5+ new customer-facing analytics features powered by the platform, while ensuring data consistency between internal and customer facing systems
Demonstrated improvement deployment velocity and cost effectiveness for data & AI use cases across engineering teams
BS or higher in Computer Science, Engineering, or a related technical field; advanced degree in AI or Data Engineering a plus
~12+ years of engineering leadership experience in cloud native SaaS and/or platform companies, including 5+ years in AI and data-intensive environments
~ Proven track record of launching enterprise capabilities leveraging AI / ML workflows including modern LLM, SLM, LAM, Reasoning, Multi-Modal based generative approaches
~ Experience designing and scaling data platforms (batch and real-time), data pipelines, and systems that power enterprise-grade AI solutions; Demonstrated ability to build and scale cross-functional teams spanning product, data and/or AI engineering
~ Experience managing global engineering organizations across multiple time zones, fostering clarity, consistency and collaboration
~ AWS, Azure, GCP) and familiarity with modern data & ML architecture paradigms
~ Nintex has a hybrid working model, enabling us to build culture, learn, and grow together. We intentionally connect and collaborate, while emphasizing flexibility with a blend of at-home and in-office work. This role is a hybrid role in our local Nintex office.
Flexible, paid time off policy
Employee wellness programs and counseling resources
Paid parental leave
Community impact, paid volunteer time, and opportunities
Multiple tools through which to learn and grow, and an incredible global community
Become apart of the Nintex team, learn about our culture, and benefits that help our people thrive.
If an offer of employment is made, this type of data may be collected through our applicant tracking system or another secure means.
- Location:
- London
- Job Type:
- FullTime