Platform Architect

Job Description

Job Description

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.