Job description

Who We Are Looking For We are seeking an AI Solution Architect, Vice President to serve as a senior technology leader responsible for shaping and driving the AI strategy for our Internal Audit function. In this role, you will provide architectural leadership to design, build, and operate production‑grade AI systems that deliver conversational, predictive, and generative capabilities at enterprise scale This is a hands‑on architectural leadership role requiring deep expertise in Generative AI , large language models (LLMs) , retrieval‑augmented generation (RAG) , AI orchestration frameworks , and enterprise integration patterns . You will partner closely with Internal Audit SMEs, data engineering, security, and infrastructure teams to ensure AI solutions are explainable, secure, compliant, and operationally resilient , while materially improving audit quality, productivity, and insight generation. What You Will Be Responsible For AI Architecture & Platform Strategy Lead the end‑to‑end architecture for AI‑enabled platforms supporting Internal Audit, integrating LLMs, machine learning models, enterprise data platforms, and core systems Define scalable, reusable architectural patterns for conversational assistants, generative insights, predictive analytics, and continuous auditing use cases Act as the technical authority for AI architecture within Internal Audit Technology, setting standards and guiding architectural decisions across initiatives AI Engineering & Orchestration Lead the design and implementation of AI orchestration frameworks to enable scalable, multi‑step reasoning and agent‑based workflows Architect solutions using frameworks such as LangChain (or equivalent) and cloud‑native capabilities (e.g., managed AI/agent services) Design workflows incorporating: Retrieval‑augmented generation (RAG) across structured and unstructured data Guardrails, validation layers, and hallucination‑mitigation techniques Define and own model selection, evaluation, and benchmarking frameworks , balancing performance, cost, latency, explainability, and risk Build & Production Operations Lead delivery of production‑ready AI systems , including model deployment, APIs, orchestration pipelines, and enterprise integrations Establish and mature LLMOps / MLOps practices , including versioning, monitoring, evaluation, logging, rollback strategies, and cost controls Ensure platforms meet enterprise standards for availability, scalability, performance, resilience, and reliability Governance, Risk & Controls Embed AI governance and model risk management into system design Implement safeguards for data privacy, security, bias detection, explainability, and auditability Partner with Internal Audit, Risk, Compliance, and Legal teams to align solutions with regulatory and internal policy requirements Use Case Enablement & Innovation Translate audit and risk challenges into high‑impact AI use cases (e.g., control testing automation, issue identification, narrative generation, continuous auditing) Guide experimentation and proof‑of‑concepts while ensuring a clear path to production Stay current on emerging AI technologies and recommend pragmatic adoption strategies What We Value The skills that will help you succeed in this role include: End‑to‑end AI architecture and solution design for enterprise, production‑grade systems Hands‑on expertise with Generative AI , including LLMs, prompt engineering, embeddings, RAG, and agent‑based workflows AI orchestration and workflow design skills for multi‑step reasoning, validation, and automation Strong engineering and operational skills to deliver scalable, reliable platforms with robust LLMOps/MLOps practices Responsible AI and governance skills , including model risk management, security, privacy, explainability, and auditability Data engineering and integration skills , leveraging enterprise data platforms, APIs, and distributed systems Analytical problem‑solving skills to translate audit and risk challenges into high‑impact AI use cases Stakeholder partnership and influence skills across audit, risk, security, and technology teams Clear technical communication and mentoring skills for technical and non‑technical audiences Continuous learning mindset to stay current with evolving AI technologies and best practices Education & Preferred Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field 10 years of experience designing and delivering enterprise software or data platforms , with 3 years focused on AI / ML solutions Hands‑on experience with large language models and modern AI frameworks (prompt engineering, embeddings, RAG, agents) Strong background in cloud platforms (Azure or AWS) and microservices‑based architectures Experience operationalizing AI systems with MLOps / LLMOps tooling and practices Solid understanding of data engineering, APIs, and distributed systems Proven ability to design systems with security, privacy, and regulatory considerations Nice to Have Experience supporting Internal Audit, Legal, or Risk Corporate functions Familiarity with model risk management or AI governance frameworks Experience with vector databases, semantic search, or enterprise data catalogs Exposure to process mining, control testing automation, or continuous auditing Cloud or AI/ML certifications Salary Range: $120,000 - $217,500 Annual The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ. Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our 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 (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans. For a full overview, visit hrportal.ehr.com . About State Street Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success. We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future. As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law. Discover more information on jobs at StateStreet.com/careers Read our CEO Statement Job Application Disclosure: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Requirements

Must-haves

Who We Are Looking For
What You Will Be Responsible For
AI Architecture & Platform Strategy
Lead the end‑to‑end architecture for AI‑enabled platforms supporting Internal Audit, integrating LLMs, machine learning models, enterprise data platforms, and core systems
Define scalable, reusable architectural patterns for conversational assistants, generative insights, predictive analytics, and continuous auditing use cases
Act as the technical authority for AI architecture within Internal Audit Technology, setting standards and guiding architectural decisions across initiatives
AI Engineering & Orchestration
Lead the design and implementation of AI orchestration frameworks to enable scalable, multi‑step reasoning and agent‑based workflows
Architect solutions using frameworks such as LangChain (or equivalent) and cloud‑native capabilities (e.g., managed AI/agent services)
Design workflows incorporating: Retrieval‑augmented generation (RAG) across structured and unstructured data
Guardrails, validation layers, and hallucination‑mitigation techniques
Define and own model selection, evaluation, and benchmarking frameworks , balancing performance, cost, latency, explainability, and risk
Build & Production Operations
Lead delivery of production‑ready AI systems , including model deployment, APIs, orchestration pipelines, and enterprise integrations
Establish and mature LLMOps / MLOps practices , including versioning, monitoring, evaluation, logging, rollback strategies, and cost controls
Ensure platforms meet enterprise standards for availability, scalability, performance, resilience, and reliability
Governance, Risk & Controls
Embed AI governance and model risk management into system design

Nice-to-haves

Education & Preferred Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field
Experience supporting Internal Audit, Legal, or Risk Corporate functions
Familiarity with model risk management or AI governance frameworks
Experience with vector databases, semantic search, or enterprise data catalogs
Exposure to process mining, control testing automation, or continuous auditing
Cloud or AI/ML certifications

Application prep

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Keywords to mirror

aimachine learningmlazureawsdesign systems

Platform: workday
Effort: long

Benefits

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Dental

Vision

401k