Head of Emerging Technology & Transformation, VP

Responsibilities

• Lead the Emerging Technology and Transformation team, setting technical direction and driving adoption of AI-first architectures
• Design and build generative AI applications using Python and modern AI frameworks
• Own end-to-end design, development, deployment, and scaling of AI solutions
• Design, develop and deploy AI solutions on Google Vertex AI
• Develop integrations with large language models, orchestration layers, prompt management, and agent-based workflows
• Identify, evaluate, and assess emerging technologies, platforms, and tools to determine their relevance, maturity, and potential enterprise value
• Stay current with industry trends across cloud infrastructure, modern application architectures, data platforms, developer tooling, automation, and integration technologies
• Conduct proofs of concept and technical evaluations to validate feasibility, scalability, security, and operational readiness of new technologies
• Contribute to technology roadmaps and modernization initiatives by identifying opportunities for platform evolution and technical transformation
• Drive responsible AI adoption by ensuring appropriate governance, model risk management, security, privacy, and regulatory compliance
• Communicate strategy, recommendations, and business impact clearly to senior stakeholders and executive leadership

• 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 Vertex AI, Azure AI, AWS AI services, or equivalent
• 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 Generative AI capabilities, including large language model integration, prompt engineering, retrieval-augmented generation, and agent-based workflows for enterprise use case
• Hands-on experience implementing embeddings and vector search for semantic retrieval within retrieval-augmented generation (RAG) architectures
• Understanding of Docker for application and workload containerization
• Monitoring of deployed models and services, including drift, skew, and performance
• 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
• Experience in financial services or highly regulated environments is preferred