VP, Global Engineering and Automation Enablement

VP, Global Engineering and Automation Enablement Role Overview
We are seeking a senior Technology Leader to own the architecture, scalability, and intelligent automation of our core FinTech platforms. This role is responsible for designing large-scale, cloud-native, distributed systems while leveraging AI-driven automation to improve platform efficiency, reliability, and operational scale.
The ideal candidate combines deep expertise in platform architecture and distributed systems with a strong point of view on using AI to automate infrastructure operations, optimize performance, and enable predictive, self-healing platforms. This is a highly technical leadership role with material influence over how the platform scales as the business grows.
VP, Global Engineering and Automation Enablement Key Responsibilities
Platform Architecture & Technical StrategyOwn the end-to-end platform architecture supporting core FinTech products and transaction flows
Define architectural standards for scalability, performance, resiliency, and system composability
Lead evolution from tightly coupled or monolithic systems toward distributed, service-oriented platforms
Establish clear system boundaries, ownership models, and architectural governance
Define and execute a multi-year platform roadmap aligned with growth, transaction scale, and product velocity
Scalability & Distributed SystemsDesign platforms capable of handling high transaction volumes, burst traffic, and sustained throughput
Guide horizontal scaling strategies across compute, storage, data, and messaging layers
Lead architectural decisions around sharding, partitioning, caching, asynchronous processing, and concurrency
Continuously improve latency, throughput, and resource efficiency across the platform
Enable multi-region and multi-environment scalability where required
Cloud & Infrastructure ArchitectureArchitect cloud platforms (AWS, Azure, or GCP) optimized for scale, availability, and operational efficiency
Define reference architectures for containerized workloads, microservices, and distributed runtimes
Lead Kubernetes and container platform adoption and standardization
Mature Infrastructure as Code (Terraform, CloudFormation, etc.) for consistent, scalable environments
Own capacity modeling, growth forecasting, and infrastructure lifecycle planning
AI-Driven Automation & Intelligent PlatformsApply AI and machine learning techniques to automate platform operations and decision-making
Use AI for:Capacity forecasting and demand prediction
Anomaly detection in platform performance and system behavior
Automated root-cause analysis and incident correlation
Predictive scaling and infrastructure optimization
Drive adoption of self-healing platform patterns where systems can respond automatically to failure or degradation
Enable data pipelines, feature stores, and runtime environments required to support AI-enabled platform services
Partner with data and engineering teams to productionize AI capabilities within core platform workflows
Platform Engineering & Developer EnablementBuild shared platform capabilities that abstract complexity and enable product teams to scale independently
Provide self-service infrastructure, golden paths, and opinionated platform tooling
Standardize CI/CD, runtime environments, observability, and deployment patterns
Reduce friction and cognitive load for application teams through strong platform design
Measure and improve developer experience as a platform outcome
Reliability, Performance & Intelligent OperationsLead SRE practices focused on scalability, automation, and operational maturity
Define and track SLIs/SLOs centered on throughput, latency, availability, and platform health
Establish advanced observability (metrics, tracing, logging) as inputs to AI-driven insights
Lead analysis of scaling failures, performance bottlenecks, and systemic inefficiencies
Drive continuous improvement toward predictable, automated, and resilient operations
Required Qualifications10+ years of experience designing and operating large-scale distributed systems
5+ years in senior technical leadership roles (Director, Principal, VP, or equivalent)
Deep expertise in platform architecture, cloud-native design, and system scalability
Strong hands-on experience with AWS, Azure, or GCP
Proven experience with microservices, event-driven architectures, and distributed data systems
Solid background in Infrastructure as Code and automation-first platform design
Experience applying AI/ML concepts to operational or platform use cases
Preferred QualificationsExperience with high-volume transaction processing or real-time systems
Strong Kubernetes and container platform experience
Experience with event streaming platforms (Kafka or equivalent)
Background modernizing legacy platforms at scale
Experience with AI-assisted operations, AIOps, or intelligent monitoring platforms
Key CompetenciesSystems-level architectural thinking with a strong scalability mindset
Ability to blend platform engineering and AI automation into practical solutions
Technical credibility with senior engineers, architects, and leadership
Pragmatic decision-maker who balances ideal architecture with real-world constraints
Strong communicator who can translate technical strategy into business impact