AI Architect Lead (Hybrid-within BankUnited's footprint)

BankUnited, Inc.•Orlando, FL

2d•Hybrid

About The Position

The AI Architect Lead is a leadership role combining strategic direction with tactical technology assessment. Reporting to the Chief Technology Officer, this position helps mature the Bank’s AI framework through thought leadership and oversight of AI-enabled application design and development. The role engages department heads, team leads, executive management, Risk and Compliance, and other stakeholders to develop AI use cases that inform the Bank’s AI adoption strategy. It bridges business and engineering teams by understanding business goals and requirements and translating them into practical AI solutions. The position also contributes to reusable AI architecture frameworks and patterns and works with Risk Management to define AI processes and controls. Candidates residing within BankUnited’s footprint may be given preference.

Requirements

Bachelor’s degree in Computer Science, Engineering, Statistics, Data Science, or a related field.
7–9 years of experience translating business requirements into technical requirements and design documents.
7–9 years of experience with application architecture analysis, design, and delivery.
4–6 years of full application development life-cycle implementations.
1–3 years of experience working with traditional AI and GenAI technologies.
1–3 years of experience in a project team lead role and road-mapping exercises.
4–6 years of banking or financial background or experience.
Excellent communication skills and business acumen.
Ability to communicate technical topics clearly, succinctly, and relevantly.
Working knowledge of AI/ML frameworks and tools.
Working knowledge of data science, data engineering, and software development principles.
Professional, positive, approachable attitude, demeanor, and discretion.
Knowledge of Agentic AI, Model Context Protocols (MCP), and LLM fine-tuning methods such as LoRA and QoRA.
Knowledge of Claude Code, frontier LLM models (GPT, Claude, Gemini), GitHub Copilot, VS Code, and Python.
Knowledge of GPU architecture, KV Cache, and token economics.
Knowledge of AWS Bedrock, M365 Copilot Studio, M365 Copilot, LangChain, Autogen, and Azure AI Foundry.

Nice To Haves

Relevant certifications in cloud AI platforms such as AWS, GCP, Azure, or Oracle, and data technologies.

Responsibilities

Collaborate with stakeholders to identify opportunities to use AI to enhance business processes and achieve desired outcomes.
Work across engineering teams to recommend appropriate AI technologies and solutions, including using synthetic data to address data drift and data quality and mitigate bias.
Understand business needs and communicate insights, findings, and requirements to engineering teams.
Conduct proofs of concept to demonstrate the value and feasibility of AI solutions to lines of business.
Advise on selecting and implementing AI technologies based on business needs and technical considerations.
Assess risks of AI solutions and recommend mitigation strategies.
Translate business requirements into realistic technical implementations and identify misaligned initiatives and impractical use cases.
Contribute to an AI architecture framework, including reusable patterns and guidelines for deploying, evaluating, and managing AI solutions.
Contribute to the Bank’s AI/ML technical direction and architectural vision, aligned with strategic goals and AI transformation efforts.
Assist in selecting open-source and commercial AI technologies, considering deployment models and integration with existing tools.
Understand LLM model architecture and evaluate its use in third-party platforms.
Contribute to successful execution of AI-powered applications using an agile methodology.
Work with security and risk leaders to identify and mitigate risks and support ethical AI implementation and compliance with upcoming regulations.
Work with the HR training department to develop and roll out AI training.
Help AI product managers and business stakeholders understand AI’s potential and limitations when planning products.
Build positive relationships with lines of business to understand their goals and objectives.
Assist with preparing AI architecture designs for Architecture Review Board approval.
Research forward-looking AI use cases and emerging technologies to inform the Bank’s AI roadmap, including machine learning and advanced LLM architectures.
Provide leadership, oversight, and guidance on AI application design and development.
Contribute to technology standards and best practices for data privacy, model security, and AI compliance, including ML and GenAI lifecycle management.
Lead the design and integration of enterprise Generative AI applications, including prompt engineering, retrieval-augmented generation, fine-tuning (LoRA, QoRA), and multimodal AI.
Lead the design and implementation of scalable MLOps/LLMOps frameworks, including model lifecycle management, CI/CD, and automated model monitoring.
Collaborate with Cloud Architecture, Security Architecture, and Enterprise Architecture to align AI solutions with enterprise standards, technology stacks, security policies, and cost-optimized cloud practices for deploying, scaling, and swapping LLMs.
Comply with applicable federal and state laws, regulations, and guidance, including anti-money-laundering requirements such as the Bank Secrecy Act and US PATRIOT Act.
Follow Bank policies and procedures and complete required training.
Identify and report suspicious activity.