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The Banking Technology Architecture Lead – NAM is a senior strategic position responsible for bridging distributed engineering teams and enterprise architecture strategy across the North America region. Operating within the Banking Technology organization, this role drives measurable delivery improvement through platform adoption, impediment resolution, and AI-first methodologies. The overall objective is to accelerate engineering delivery velocity by embedding architectural best practices and intelligent, data-driven decision-making at the team level — with AI serving as the primary force multiplier for regional impact.
Job Responsibility:
Drive measurable adoption of Citi Manifesto principles, Golden Paths, and Foundational platforms across NAM engineering teams
Translate enterprise architecture vision into practical, actionable guidance that accelerates delivery velocity
Achieve quantifiable adoption metrics through hands-on enablement and demonstration of platform value
Leverage AI-powered analytics to identify adoption patterns, surface friction points, and personalize enablement strategies for different team contexts and maturity levels
Build trusted relationships with engineering team leads by acting as a visible, accessible partner — not an oversight function — to encourage voluntary adoption of architectural standards
Systematically collect, document, and analyze real engineering bottlenecks and recurring delivery obstacles using AI-driven analysis across incident reports, delivery metrics, and workflow telemetry
Deploy AI-powered delivery analytics tools to identify lead time bottlenecks across the full software delivery lifecycle — spanning planning, development, testing, and deployment
Champion an AI-first approach to continuous improvement, ensuring all recommendations are grounded in data and augmented by intelligent tooling rather than anecdotal observation
Maintain reliable, cadenced communication with the Head of Architecture (weekly/bi-weekly), providing structured updates on impediments, adoption progress, and improvement outcomes
Manage enterprise architecture processes to ensure they enhance — rather than hinder — delivery velocity
Provide data-driven evidence of lead time improvements attributable to architecture initiatives, using AI-generated insights and delivery dashboards where applicable
Ensure AI tools and analytics platforms adopted within the architecture function comply with enterprise AI governance standards, including explainability, fairness, and data privacy requirements — collaborating with risk, legal, and compliance teams as needed
Requirements:
8+ years in software engineering, platform engineering, or enterprise architecture roles, with 3+ years in a senior or lead capacity
Demonstrated experience driving platform or tooling adoption across distributed engineering teams
Proven AI-first mindset: hands-on, day-to-day experience using AI tools, analytics platforms, or LLM-based solutions to improve engineering workflows, delivery metrics, or decision-making — this is a non-negotiable requirement
Strong analytical skills with the ability to translate delivery telemetry and impediment data into actionable architectural recommendations
Familiarity with DORA metrics and software delivery lifecycle performance frameworks (lead time, cycle time, deployment frequency, change failure rate)
Experience working across cross-functional teams including DevOps, platform engineering, and developer experience functions
Excellent communication and stakeholder management skills, with a demonstrated ability to influence without direct authority — essential given the embedded liaison operating model
Bachelor's degree in Computer Science, Engineering, or equivalent experience
Familiarity with enterprise architecture frameworks (e.g., TOGAF, C4 Model) and their practical application in large-scale organizations
Prior exposure to Golden Path or Internal Developer Platform (IDP) programs
Experience with observability, platform telemetry, and engineering metrics dashboards
Familiarity with engineering maturity models or capability assessments used to benchmark team adoption and delivery performance
Exposure to enterprise AI governance standards, including model explainability, fairness, and compliance frameworks
Advanced degree in Computer Science, Systems Engineering, or a related technical field
What we offer:
Play a pivotal role in shaping how enterprise architecture is practiced across one of the world's largest financial institutions
Be at the forefront of AI-augmented architecture practice — helping define how AI tools reshape the way enterprise engineering teams design, build, and deliver software at scale
Work at the intersection of engineering delivery, platform strategy, and cutting-edge AI tooling
High visibility with architecture leadership and engineering teams across NAM and EMEA
Access to world-class AI platforms, delivery analytics infrastructure, and a culture committed to continuous improvement
Drive real, measurable impact on how hundreds of engineers deliver software every day