Application & AI Solutions Architect, Vice President

Who we are looking for

We are looking for an experienced technology leader and solutions architect with deep expertise in data engineering, enterprise application development, solution architecture, and artificial intelligence, combined with strong financial-services domain knowledge.

The successful candidate will provide technical leadership across strategic platforms supporting Repo, Collateral Management, Asset Management, Custody, Securities Lending, Fixed Income, and related Global Markets functions. The role requires the ability to translate complex business requirements into scalable technology solutions, lead architecture and design decisions, guide engineering teams, and drive delivery across data, application, and AI initiatives.

The individual should be equally comfortable engaging with senior business stakeholders, defining future‑state architecture, and working with engineering teams on detailed technical design and implementation.

• Lead solution architecture, technical design, and engineering strategy for complex financial‑services applications and data platforms, translating business objectives into scalable target‑state solutions.
• Partner with business leaders, product owners, operations, architecture, and engineering teams to define requirements, develop technology roadmaps, perform solution estimation, and build executable project and implementation plans.
• Design and modernize enterprise applications using microservices, Spring Boot, APIs, Kafka, MQ, Oracle/Exadata, Python, and distributed data‑processing technologies, with focus on scalability, resiliency, performance, and maintainability.
• Lead design of enterprise data architectures, data models, ETL/ELT pipelines, real‑time integrations, CDC solutions, and analytical platforms using technologies such as Oracle, Databricks, Snowflake, Kafka, and related data‑engineering frameworks.
• Provide hands‑on technical direction across Python, SQL, PL/SQL, Perl, database engineering, application development, performance tuning, and enterprise integration, including architecture and code reviews for critical systems.
• Identify and architect opportunities to apply Generative AI, Retrieval‑Augmented Generation (RAG), Agentic AI, OCR/vision models, and intelligent automation to complex financial‑services and operational workflows.
• Design enterprise AI solutions that integrate LLMs, trusted business data, APIs, application workflows, and human‑in‑the‑loop controls, ensuring responses and actions are grounded, traceable, and aligned with business requirements.
• Establish technical patterns for AI governance, guardrails, functional and non‑functional evaluation, observability, monitoring, security, and responsible deployment of AI and agentic applications.
• Drive adoption of AI‑assisted engineering practices to improve software‑development productivity, testing, analysis, and operational support while maintaining appropriate enterprise controls.
• Lead and mentor distributed engineering teams, provide technical and functional guidance, and act as a senior escalation point for complex application, data, and production issues.

• Strong hands‑on expertise in Python, SQL, PL/SQL, Oracle Database/Exadata, data modeling, ETL/ELT, data engineering, Databricks, Snowflake, Kafka, MQ, Spring Boot, microservices, APIs, and enterprise data‑integration patterns; working knowledge of Perl and related development technologies.
• Experience designing high‑performance enterprise applications, real‑time and batch data pipelines, data warehouses/lakehouse platforms, CDC solutions, distributed architectures, and scalable financial‑data processing systems.
• Strong practical knowledge of Generative AI, LLMs, RAG, Agentic AI,…