AVP AI Solutions Management

About our client:

Our client operates in the consumer financial services space, focusing on making everyday purchases and essential needs more accessible through flexible financing solutions. They support individuals across their financial journey—from obtaining their first line of credit to managing long-term financial flexibility—by enabling more informed and responsible credit decisions.

Our client has built a vast network that connects consumers with a wide range of small and mid-sized businesses, as well as providers in the health and wellness sector. Through this ecosystem, they play a meaningful role in supporting both customer financial well-being and the growth of businesses that form a critical part of the broader economy

Responsibilities:

• Support the AI use-case intake process, gather requirements, and rapidly assess strategic fit, value, complexity, and feasibility.
• Maintain an AI use-case/solution inventory; identify duplication and promote reuse of existing platforms and components.
• Evaluate alignment to the company’s AI strategy, enterprise architecture, data strategy, and target operating model.
• Help establish guidelines for build/buy/hybrid and create recommendation artifacts for leadership and governance bodies.
• Assess candidate architectures across cloud services, data platforms, model choices (LLMs, classical ML, CV, NLP), and integration patterns.
• Compare third-party SaaS/managed services with in-house custom builds and hybrids; estimate TCO, scalability, maintainability, and time-to-value.
• Support vendor evaluations and small proof-of-concept efforts, reviewing items like security practices, data handling, SLAs, integration needs, and roadmap alignment.
• Partner with Procurement/Vendor Management on contracting, licensing, data processing, and exit strategies.
• Partner with Engineering, Data Science, and DevOps/MLOps to scope pilots and define success metrics and guardrails.
• Ensure handoffs include documentation, controls, and operational readiness
• Develop playbooks, patterns, and templates to support AI solution reviews, and help enable business and tech teams through training sessions and office hours..
• Track portfolio outcomes (benefits, risk findings, reuse rate) and continuously improve intake and evaluation processes.

Requirements:

• Software engineering and cloud architecture knowledge across AWS/Azure; APIs; event/microservices; observability.
• Good understanding of AI/ML and LLM stacks (vector databases, embeddings, RAG, prompt engineering, guardrails).
• Understanding of privacy/security controls in financial services (data classification, encryption, DLP, IAM, segmentation) and third-party risk.
• Proven ability to translate business objectives into technical evaluation criteria and clear decisions.
• Excellent written and verbal communication for executive-level summaries and deep-dive technical reviews.
• Critical thinker with structured problem-solving and sound judgment