Head of Enterprise Architecture, SVP

State Street • Quincy, MA

4d • $225,000 - $337,500

About The Position

The Head of Enterprise Architecture owns the target-state design of the technology estate and the standards, patterns and governance through which it is realised. This is the architectural blueprint that determines how every platform, application and integration in the firm is built, connected, secured and retired. The mandate is to reduce complexity while increasing optionality — cutting technical debt, rationalising a fragmented estate, and establishing the reusable architectural foundations that let engineering teams move faster within known-good boundaries. Success is measured not in documents published but in estate outcomes: fewer bespoke solutions, faster architectural decisions, demonstrably lower run cost, and an architecture capable of absorbing the pace of change that Frontier AI and post-quantum cryptography will impose. A central element of this mandate is establishing the architecture that makes the firm AI-forward — the compute, serving, integration and control foundations on which AI becomes a governed production capability rather than a portfolio of experiments. This is delivered in deliberate partnership with the Head of Data & AI, who owns model strategy, data products and AI delivery. This is a deeply technical leadership role. The successful candidate is a credible principal-level architect who has personally designed systems at scale, and who will lead through technical authority rather than positional mandate — equally effective authoring a reference architecture, defending a standard to a skeptical business-unit CIO, and presenting an estate rationalization case to the Senior Leadership.

Requirements

• Extensive, hands-on engineering and architecture career culminating in principal-architect or enterprise-architecture leadership roles, with demonstrable personal technical depth — not solely management tenure.
• Proven delivery of enterprise-wide architecture programmes across multi-cloud and hybrid estates at material scale, including responsibility for target-state definition and its realisation.
• Deep expertise across cloud-native architecture, Kubernetes, distributed systems, event streaming, API and integration patterns, infrastructure-as-code and zero-trust security architecture.
• Demonstrable depth in AI infrastructure architecture — model serving and inference optimisation, accelerated-compute cluster design, vector store selection and design, retrieval patterns and AI observability — sufficient to set standards and evaluate engineering decisions credibly.
• Working knowledge of AI governance architecture: model risk tiering, explainability tooling, data provenance controls and audit-trail design for AI-assisted decisions.
• A track record of earning architectural adoption through influence and demonstrated value across a large, federated, sometimes skeptical organisation.
• Executive presence: able to defend standards alongside senior engineers, and investment and rationalisation cases to senior leadership audiences, with equal authority.

Nice To Haves

• Financial-services or comparably regulated experience, with working knowledge of SR 11-7, DORA, FFIEC, BCBS 239 or OCC Heightened Standards, and awareness of EU AI Act risk classification.
• Experience building an enterprise pattern library from a standing start and demonstrably reducing time-to-architectural-decision.
• Experience defining an AI reference architecture adopted across multiple product teams, moving AI from isolated proofs of concept to governed production capability.

Responsibilities

• Own the enterprise technology blueprint across infrastructure, cloud, security, data and application domains; maintain a coherent target state aligned to long-term business strategy.
• Chair the Technology Standards Board and own the EARB / SARB review mechanisms — running governance through decision logs, fitness functions and time-boxed exception processes that operate at delivery speed.
• Partner with business-unit technology leaders to prevent domain-level decisions creating enterprise-wide integration debt; clearly delineate architecture accountability from engineering execution.
• Define, curate and govern the enterprise pattern library across infrastructure, cloud, integration, security and AI/ML domains, with a formal maturity model (Emerging / Validated / Strategic / Deprecated).
• Drive active extraction of patterns from production systems — converting institutional knowledge into documented, reusable assets rather than commissioning them in the abstract.
• Publish a quarterly Technology Radar translating market signal into firm guidance on adopt, trial, assess and hold positions, with named executive accountability for retiring end-of-life technologies.
• Define the AI infrastructure reference architecture — accelerated compute, model serving, inference optimisation, AI gateway and access-governance patterns — providing the substrate on which the Data & AI organisation delivers models and AI products.
• Establish enterprise architectural standards for agentic systems: orchestration topology, tool-use patterns, human-in-the-loop escalation, and audit-trail requirements for AI-assisted decisions in regulated workflows.
• Own the architectural control framework for AI — risk tiering, explainability requirements by use case, data provenance controls and output governance — ensuring deployments satisfy SR 11-7, EU AI Act and emerging supervisory expectations, jointly with the Head of Data & AI and the CISO.
• Build the approved AI integration pattern set (RAG, document intelligence, structured output generation, model-in-the-loop workflows) so engineering teams build on validated foundations without bespoke review.
• Build cost transparency models mapping vendor spend, cloud consumption and accelerated-compute cost to platform capability and delivered business value; benchmark against peer institutions.
• Lead estate rationalisation reviews identifying consolidation opportunities, renewal risk, vendor concentration and underutilised assets.
• Establish the unit economics of AI infrastructure — the crossover analysis between on-premise GPU, cloud instances and foundation-model API consumption — to enable rational capital allocation.
• Build and lead a global enterprise and domain architecture team, substantially formed by consolidating distributed architecture capability, supplemented by targeted external hires.
• Establish an architecture community of practice that scales influence into engineering teams without proportionate headcount growth; mentor senior engineers into architecture career paths.

Benefits

• retirement savings plan (401K) with company match
• insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
• paid-time off including vacation, sick leave, short term disability, and family care responsibilities
• access to our Employee Assistance Program
• incentive compensation including eligibility for annual performance-based awards
• eligibility for certain tax advantaged savings plans
• inclusive development opportunities
• flexible work-life support
• paid volunteer days
• vibrant employee networks

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed