Position Summary We are seeking an experienced AI Architect with a proven background in asset and wealth management to design and lead enterprise-grade AI/ML solutions across the investment lifecycle. This individual will translate complex business needs - portfolio construction, risk analytics, client advisory, and regulatory reporting - into scalable, secure, and compliant AI architectures. The ideal candidate combines deep technical expertise in machine learning, data engineering, and cloud architecture with firsthand knowledge of asset managers, wealth advisors, and institutional investors, engaging credibly with both technology teams and front-office stakeholders.
Key Responsibilities AI/ML Architecture & Strategy- Define AI/ML roadmap with reference architectures, design patterns, and technology standards.
- Partner with engineering teams to deliver a cohesive, production-ready AI ecosystem.
- Evaluate build-vs-buy decisions for AI/ML platforms, LLM tooling, and vendor solutions.
- Solution Design & Delivery
- Architect end-to-end AI/ML solutions for portfolio optimization, risk modeling, credit/liquidity analytics, robo-advisory, and client recommendations.
- Design generative AI workflows for research summarization, memo drafting, client reporting, and advisor productivity.
- Establish MLOps pipelines ensuring reliable model deployment with monitoring and rollback.
- Oversee data architecture across market data, custodial, CRM, and portfolio accounting systems.
- Governance, Risk & Compliance
- Embed model risk governance including explainability, bias testing, and auditability.
- Ensure regulatory compliance for AI systems handling MNPI, client PII, and proprietary data.
- Partner with Compliance for validation, documentation, and independent review.
- Leadership & Stakeholder Engagement
- Mentor technical teams including data scientists, ML engineers, and quantitative developers.
- Serve as trusted advisor to investment professionals and technology leadership.
- Evaluate emerging AI/ML trends and present recommendations to executives.
Required Qualifications - Bachelor's degree in Computer Science, Data Science, Engineering, Finance, or related field (Master's/MBA preferred).
- 12+ years of progressive technology experience, with 5+ years in AI/ML architecture for financial services.
- Domain background in asset/wealth management, private banking, hedge funds, or fintech.
- Knowledge of investment lifecycle processes and AI value creation.
- Hands-on proficiency in Python, SQL, ML/DL frameworks (PyTorch, TensorFlow, scikit-learn).
- Experience with LLM frameworks (LangChain, LlamaIndex) and vector databases.
- Cloud expertise: AWS SageMaker, Azure ML, Google Vertex AI.
- Data platforms: Snowflake, Databricks, Spark, Kafka.
- Strong understanding of model risk management, governance, and regulatory frameworks (SR 11-7, GDPR/CCPA, SEC/FINRA).
- Excellent communication and presentation skills.
Preferred Qualifications - C ertifications: AWS/Azure/GCP AI Architect, CFA, FRM, or CAIA.
- Familiarity with quantitative finance concepts (factor models, portfolio optimization, VaR, asset allocation).
- Experience productionizing generative AI/agentic applications.
- Experience in regulated financial services environments and enterprise design authorities.
Core Competencies - Strategic Systems Thinking - translates ambiguous business problems into scalable designs.
- Pragmatic Judgment - balances innovation with cost and compliance.
- Cross-Functional Influence - builds credibility with engineers and investment professionals.
- Risk & Governance Fluency - navigates compliance confidently.
- Continuous Learning - stays current with AI/ML and generativ e AI trends.
