About the Opportunity
A leading global investment management firm is seeking an Enterprise AI Architect to help define and accelerate the organization's enterprise-wide AI strategy. This is a highly visible role that will partner closely with executive leadership and enterprise architecture teams to establish the architectural foundations for AI adoption across a complex global organization.
The successful candidate will be responsible for developing AI architecture standards, governance frameworks, and enterprise-wide design patterns that enable secure, scalable, and responsible AI deployment across investment, operational, and client-facing functions.
This is a unique opportunity to influence how a major financial institution leverages emerging AI technologies to drive innovation, efficiency, and competitive advantage.
Key Responsibilities
Enterprise AI Strategy & Architecture
- Define and maintain the enterprise AI architecture roadmap, including model infrastructure, data platforms, orchestration layers, integration patterns, and governance controls.
- Develop reference architectures for agentic AI systems, multi-agent workflows, orchestration frameworks, and Model Context Protocol (MCP)-based implementations.
- Design AI solutions supporting front-, middle-, and back-office business functions.
- Drive integration of AI capabilities with enterprise data and content platforms utilizing RAG, vector databases, embeddings, and modern AI tooling.
- Establish standards for AI platform scalability, security, and operational excellence.
Governance, Risk & Compliance
- Design and operationalize AI governance frameworks covering model risk management, explainability, bias monitoring, data lineage, and regulatory compliance.
- Define evaluation criteria for foundation models and open-source models, balancing performance, cost, latency, security, and business value.
- Partner with Legal, Risk, Compliance, and Information Security teams to ensure responsible AI deployment.
- Develop security and privacy patterns addressing prompt injection, sensitive data handling, and regulatory requirements.
Enterprise Leadership
- Translate business objectives into AI architecture roadmaps and technology strategies.
- Guide architecture review processes and provide governance for AI-related initiatives.
- Produce executive-level deliverables including technology assessments, architecture blueprints, vendor evaluations, and strategic recommendations.
- Serve as a trusted advisor to technology and business leadership on AI opportunities and risks.
Innovation & Emerging Technologies
- Monitor advancements in generative AI, agentic systems, foundation models, AI infrastructure, and related technologies.
- Lead proof-of-concept initiatives and establish frameworks for evaluating emerging capabilities.
- Maintain relationships with leading technology vendors, cloud providers, research organizations, and industry groups.
- Identify opportunities to leverage emerging technologies to create strategic business value.
Team Development & Mentorship
- Mentor architects and engineering teams on AI design patterns and best practices.
- Contribute to the evolution of enterprise architecture standards and methodologies.
- Promote AI literacy and architectural excellence across the organization.
- Represent the organization at industry conferences, architecture forums, and technology communities.
Qualifications
Required
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related discipline.
- 10+ years of technology architecture experience, including 3–5+ years focused on AI/ML architecture in large enterprise environments.
- Deep hands-on expertise with modern AI technologies including:
- Large Language Models (LLMs)
- RAG architectures
- Vector databases
- Embedding pipelines
- Prompt engineering
- Agent orchestration frameworks such as LangChain, AutoGen, CrewAI, or similar
- Experience designing agentic AI solutions and multi-agent architectures.
- Strong background with enterprise data platforms such as Snowflake, Databricks, or similar technologies.
- Experience building cloud-native architectures within AWS environments, including AI/ML services.
- Ability to create architecture artifacts including reference architectures, technology roadmaps, architectural decision records, and capability assessments.
- Experience working within formal enterprise architecture governance processes.
- Exceptional communication and stakeholder management skills.
Preferred
- Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
- Experience within financial services, asset management, investment banking, fintech, or other highly regulated industries.
- Knowledge of AI governance frameworks, model risk management, and evolving AI regulations.
- Familiarity with emerging technologies including quantum computing, blockchain, distributed ledger technologies, and advanced AI infrastructure.
Additional Information
- Full-time position.
- Candidates must be authorized to work in the United States without current or future sponsorship requirements.
- Opportunity to play a key role in shaping enterprise AI strategy at a globally recognized financial institution.