Corporate Vice President - Full Stack Engineering Lead - AI & Emerging Technologies
$147,500–$211,000 year
Remote
Job Summary
Design and deliver high-impact full stack solutions using emerging technologies like AI, advanced automation, and modern data platforms. Architect, lead, and mentor engineering teams to build scalable, secure platforms that enhance developer experience while reducing onboarding friction. Define and execute strategies for AI and GenAI use cases, including Agentic AI, and run pilots to integrate reusable assets into enterprise operations. Collaborate with data scientists, security teams, and business leaders to translate domain challenges into innovative solutions that align with enterprise architecture standards. Identify and mitigate ethical, legal, and security risks associated with AI systems while balancing speed-to-market with technical quality.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Systems Analysis, or a related field (or equivalent experience and certifications)
- 8+ years of experience in full stack engineering and architecture, including AI and GenAI solutions
- Strong experience in software architecture, engineering best practices, and technology governance
- Hands-on experience with front-end technologies such as React, Angular, and JavaScript
- Hands-on experience with back-end technologies such as Java, Spring Boot, Node.js, and C#
- Experience with AI frameworks such as TensorFlow and PyTorch
- Proficiency in Python and experience with AI orchestration frameworks such as LangChain
- Experience with vector databases, knowledge graphs, and modern data processing techniques
- Strong understanding of Agile development methodologies, DevSecOps practices, and CI/CD pipelines
- Experience with Infrastructure as Code (e.g., Terraform)
- Cloud platform experience, preferably AWS
- Deep understanding of architectural patterns, principles, and frameworks
- Strong analytical skills with the ability to connect technical solutions to business outcomes
Desired Qualifications
- Experience delivering end-to-end AI solutions, including data ingestion, vectorization, model integration, and deployment platforms
- Experience implementing enterprise platforms such as content management systems, low-code platforms, or application builders
- Knowledge of security protocols and secure system design
- Financial services industry experience
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