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 Requirements 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 #J-18808-Ljbffr Jobtailor