CX Emerging Technology Architect, Vice President
On-siteBengaluru, Karnataka, India
Job Summary
Architect and implement scalable AI solutions incorporating Large Language Models, Retrieval-Augmented Generation, and vector databases using Python and Google Gemini Enterprise. Define and execute the emerging technology and AI capability roadmap, evaluating platforms to balance innovation with security and operational excellence. Design cloud-native applications and lead a high-performing team of AI engineers and solution architects to deliver production-grade business transformation. Partner with global business, security, and infrastructure teams to drive responsible AI adoption and modernization initiatives within a highly regulated financial services environment.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical discipline
- Overall, 10+ years of work experience
- Strong, hands-on expertise in Python for building production-grade applications and AI solutions
- Experience with enterprise AI platforms such as Google Gemini Enterprise, Azure AI, AWS AI services, or equivalent, with the ability to evaluate and adopt platforms based on enterprise needs
- Proven experience defining AI and emerging technology strategy, including platform selection, build vs buy decisions, and alignment with enterprise architecture standard
- Experience with Cloud services such as Compute Engine, Cloud Storage, Cloud Run, IAM etc
- Experience designing, building, and scaling AI capabilities, including large language model integration, prompt engineering, retrieval‐augmented generation, and agent‐based workflows for enterprise use case
- Solid understanding of software development lifecycle and enterprise-grade engineering practices
- Experience designing cloud-native and scalable application architectures
- Experience with data platforms, APIs, and integration patterns
Desired Qualifications
- Experience in financial services or highly regulated environments is preferred
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