For additional information, please review .The ideal candidate will be **deeply AI-first in their thinking and practice**, leveraging AI-powered tools, analytics, and automation as a primary force multiplier to drive adoption of standardized platforms, reduce lead times, and deliver data-driven architectural recommendations at scale. **AI fluency is not optional — it is a core success factor for this role.** Candidates who do not actively use and champion AI tooling in their day-to-day practice will not be competitive for this position.* 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.* Engineering Team Leads (Global)* Platform Engineering Teams* DevOps/Tooling Organizations* Enterprise Architecture Function* Developer Experience Teams* **AI Platform Teams** (for tool integration and AI capability enablement)* Data Analytics Teams (for delivery metrics and insights)* Business / Product Stakeholders (for upstream architecture impact alignment)**Operating Model:** Embedded liaison with dotted-line relationships to engineering teams and solid-line accountability to architecture leadership — with **AI as a deliberate and non-negotiable force multiplier for regional impact**. This role does not govern through authority; it leads through insight, enablement, and demonstrated value.* **AI-powered analytics and tooling are embedded into the architecture function's day-to-day operations**, not treated as an afterthought — the candidate actively models AI-first behavior for the broader engineering community.* Engineering teams demonstrate **measurable, quarter-over-quarter reductions in lead time**, directly attributable to architecture enablement and AI-driven recommendations, tracked via delivery telemetry and reported to architecture leadership.* Golden Paths and Foundational platform adoption rates increase quarter-over-quarter, with telemetry data validating impact.* Impediment documentation is timely, actionable, and consistently drives **systemic improvements** rather than one-off fixes.* Architecture governance processes are perceived by engineering teams as **accelerators, not blockers**.* Engineering teams proactively engage the Architecture Lead as a trusted partner, evidenced by inbound requests for guidance and collaboration.* The role serves as a **visible champion of AI-first engineering culture** across the NAM region, inspiring teams to adopt intelligent tooling as a standard practice.* 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.* **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* Master's degree preferred* Experience with AI-powered developer tooling, delivery analytics platforms, or intelligent automation frameworks (e.g., GitHub Copilot, AI-assisted observability tools, LLM-based workflow automation).* 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.#J-18808-Ljbffr