Chief Technology Officer

About the Role

GuidedChoice is searching for a visionary engineering leader who excels in both high-level strategy and hands-on technical expertise to spearhead technology innovation within the financial services and wealth management technology sector. This leadership position entails overseeing software development, system architecture, cloud infrastructure, AI projects, security measures, and engineering operations.

Key Responsibilities

• Define and implement the company’s technology vision, architectural strategy, and engineering roadmap in alignment with overall business objectives.
• Collaborate with executive leadership to integrate technology initiatives that enhance business outcomes.
• Investigate and adopt cutting-edge technologies, including AI platforms and tools, to gain a competitive edge.
• Set engineering standards, secure development policies, and governance protocols to ensure platform reliability, scalability, and security.
• Lead and nurture a high-performance engineering team, fostering accountability, innovation, and growth through mentorship, career development, and talent acquisition.
• Manage project priorities, resource distribution, and delivery timelines effectively to meet organizational goals.
• Oversee the architecture and development of web, mobile, API, and backend systems ensuring they are scalable, maintainable, secure, and aligned with long-term business goals.
• Serve as a key technical advisor, conducting architecture reviews, code assessments, and resolving complex engineering issues.
• Drive AI adoption by designing and managing AI-powered systems using LLMs, vector databases, workflow automation, and orchestration frameworks, ensuring compliance and security in financial contexts.
• Administer cloud infrastructure primarily on Microsoft Azure, emphasizing operational excellence, scalability, disaster recovery, and modern DevOps practices including Infrastructure-as-Code and CI/CD pipelines.
• Ensure adherence to financial industry security standards and regulatory compliance through cross-functional partnerships and secure software lifecycle management.

Qualifications

• Undergraduate degree in Computer Science, Software Engineering, or related technical discipline.
• Minimum 10 years of professional software engineering experience, including at least 5 years in leadership roles managing engineering teams or large technical initiatives.
• Proven track record building and scaling enterprise SaaS platforms.
• Direct experience developing production-level AI solutions.
• Strong backend development skills with Java, Spring Boot, microservices, and API design expertise.
• Comprehensive understanding of distributed systems, cloud-native applications, and enterprise software architecture.
• Extensive experience with Microsoft Azure cloud services and related DevOps practices such as containerization and CI/CD pipelines.
• Exceptional communication capabilities with the ability to present effectively at the executive level.

Preferred Experience

• Previous roles such as CTO, VP of Engineering, Director of Engineering, or Principal Architect preferred.
• Background in financial services, wealth management, fintech, retirement planning, or other highly regulated sectors.
• Familiarity with advanced AI platforms including Azure OpenAI, OpenAI APIs, Anthropic, Google Gemini, or similar.
• Experience with Kubernetes, Infrastructure as Code (e.g., Terraform), event-driven architectures, and messaging systems.
• Expertise implementing enterprise security frameworks and compliance programs.
• Knowledge of React, React Native, and modern frontend architectural principles.

Leadership Attributes

• Strategic mindset balancing innovation with pragmatic execution.
• Comfortable bridging executive leadership with engineering teams.
• Dedicated mentor and talent developer with a strong ownership mentality and proactive decision-making skills.
• Passionate about emerging technologies, AI advancements, and product innovation.

First-Year Success Milestones

• Develop an in-depth understanding of the company’s business, products, customers, and technology landscape.
• Enhance engineering standards, governance, and architectural frameworks.
• Optimize cloud and AI system architectures for performance and scalability.
• Formulate and execute a comprehensive AI strategy across the organization.
• Increase engineering team productivity, quality, and operational efficiency.