At a Glance
- Tasks: Lead AI architecture and strategy, driving firm-wide AI adoption and governance.
- Company: Join T. Rowe Price, a leader in financial services with a focus on innovation.
- Benefits: Enjoy hybrid work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with top professionals and mentor future architects in a dynamic setting.
- Why this job: Be at the forefront of AI transformation in a global institution and make a real impact.
- Qualifications: 10+ years in tech architecture, with 3-5 years focused on AI/ML in complex environments.
The predicted salary is between 80000 - 100000 £ per year.
At T. Rowe Price, the mission of the Enterprise Architecture (EA) function is to empower the firm to achieve its strategic objectives through optimal use of technology. As Enterprise AI Architect, you will be at the forefront of firm‑wide AI activation, working directly with the Chief Architect to define, govern, and accelerate AI adoption across a complex, global institution, translating ambitious strategy into concrete architectural blueprints that are coherent, scalable, secure, and aligned with fiduciary obligations.
Responsibilities
- AI Architecture & Strategy: Define and maintain the Enterprise AI Architecture spanning model infrastructure, data pipelines, orchestration layers, integration patterns, and governance controls. Develop reference architecture for agentic AI systems and multi‑agent workflows, establishing standards for MCP and model‑context protocols. Create AI reference architectures for investment and front‑to‑back office use cases. Drive integration of AI capabilities with core data platforms and content platforms, leveraging RAG and MCP to unlock proprietary data assets.
- Governance & Risk: Design and operationalize AI governance, covering model risk management, explainability, bias monitoring, data lineage, and regulatory compliance. Evolve model evaluation and selection criteria for frontier and open‑weight models, balancing capability, performance, cost, and latency. Partner with Legal, Compliance, and Risk to embed AI risk controls into architecture review processes. Define data privacy and security patterns for AI workloads.
- Enterprise Alignment & Stakeholder Leadership: Translate business strategies from investment, distribution, finance, and operations into AI architecture requirements and roadmaps. Guide the Architecture Review Board (ARB) for AI proposals. Produce executive‑grade artifacts—technology radars, strategic assessments, vendor evaluations, ADRs—to serve as an AI thought leader and trusted advisor.
- Technology Scanning & Innovation: Operate continuous scanning of frontier AI developments and distill insights for senior leadership. Evaluate and pilot emerging AI capabilities with clear proof‑of‑concept criteria. Maintain relationships with AI vendors, cloud hyperscalers, research institutions, and peer firms for benchmarking.
- Team, Collaboration & Community: Mentor architects and engineers on AI design patterns and responsible AI practices. Contribute to Enterprise Architecture practice development, including standards and templates, and represent the firm in external AI forums and industry groups.
Qualifications
- Bachelor’s degree in computer science, engineering, mathematics, statistics, or related fields.
- 10+ years in technology architecture, 3–5 years focused on AI/ML architecture in large, complex enterprise environments.
- Hands‑on command of modern AI stack: LLM APIs and fine‑tuning, vector databases, RAG, embedding pipelines, prompt engineering, and agent orchestration frameworks (LangChain, AutoGen, or equivalents).
- Practical exposure to agentic AI architecture, multi‑agent coordination, and MCP or similar frameworks.
- Experience with enterprise data platforms (Snowflake, Databricks, or comparable) and integrating AI on top of them.
- Strong understanding of cloud‑native architecture on AWS, including AI/ML services such as Bedrock.
- Ability to produce high‑quality architecture artifacts—reference architectures, technology radars, ADRs, capability assessments.
- Familiarity with enterprise architecture frameworks such as TOGAF and operation within Architecture Review Boards.
- Excellent communication skills, synthesizing complex technical topics for non‑technical stakeholders.
Preferred
- Master’s or PhD in Computer Science, AI, ML, Data Science, or related field.
- Experience in financial services (asset management, investment banking, fintech) with knowledge of investment workflows, data governance, and regulatory obligations.
- Knowledge of AI governance frameworks, model risk management guidelines, and emerging AI regulations.
- Familiarity with emerging AI‑adjacent technologies: quantum computing for AI, blockchain/DLT, etc.
Work Flexibility
This role is eligible for hybrid work, with up to three days per week from home.
Enterprise AI Architect employer: T. Rowe Price
At T. Rowe Price, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. As an Enterprise AI Architect, you will have the opportunity to work at the cutting edge of technology within a supportive environment that values professional growth and mentorship. Our commitment to employee development, combined with our hybrid work model, ensures that you can thrive both personally and professionally while contributing to meaningful projects in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Enterprise AI Architect
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to AI architecture. We suggest doing mock interviews with friends or using online platforms to get comfortable with articulating your experience and skills.
✨Tip Number 3
Showcase your expertise! Create a portfolio of projects or case studies that highlight your work in AI architecture. This will give potential employers a tangible sense of your capabilities and how you can contribute to their team.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Enterprise AI Architect
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with AI architecture and strategy. We want to see how your skills align with our mission at T. Rowe Price, so don’t hold back on showcasing relevant projects!
Showcase Your Technical Skills:When detailing your experience, focus on the modern AI stack and any hands-on work you've done with LLM APIs, vector databases, or cloud-native architecture. We’re keen to see your technical prowess, so be specific about your achievements!
Communicate Clearly:Remember, you’ll need to explain complex technical topics to non-technical stakeholders. Use clear and concise language in your application to demonstrate your communication skills. We love a good storyteller!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!
How to prepare for a job interview at T. Rowe Price
✨Know Your AI Architecture Inside Out
Make sure you’re well-versed in the specifics of AI architecture, especially the modern AI stack. Brush up on LLM APIs, vector databases, and agent orchestration frameworks like LangChain. Being able to discuss these topics confidently will show that you’re not just familiar with the concepts but can also apply them effectively.
✨Prepare for Governance Questions
Given the importance of governance in this role, be ready to discuss model risk management, explainability, and data privacy. Think about how you would operationalise AI governance and what best practices you would implement. This will demonstrate your understanding of the regulatory landscape and your ability to navigate it.
✨Showcase Your Communication Skills
You’ll need to translate complex technical topics for non-technical stakeholders, so practice explaining your past projects in simple terms. Use examples that highlight your ability to communicate effectively across different teams, especially when discussing AI strategies and architectures.
✨Demonstrate Your Collaborative Spirit
This role involves mentoring and collaborating with various teams, so be prepared to share experiences where you’ve successfully worked with others. Highlight any leadership roles or initiatives you’ve taken to foster teamwork, especially in AI-related projects. This will show that you’re not just a tech whiz but also a team player.
