Assistant VP

Responsibilities: Program Leadership Define the delivery plan and drive execution per strategy / roadmap (SG and regionally). Obtain buy-in / approval from senior management and stakeholders for planned execution. Foster collaboration with key stakeholders across units/ teams (including auditors) to Develop and maintain project documentation, including project plans, risk assessments, and status reports. Ensure that implementation actions and challenges are identified and addressed effectively. Responsible for leadership and regulatory updates (e.g. Steering Committee meetings) to provide visibility on project milestones and status to drive key decisions. Ability to link technicalities to strategic intent Lead strategic programs that integrate platform operating models and journey-focused methodologies, ensuring cohesive, end-to-end delivery across our technology landscape. Effectively manage and influence stakeholders with competing priorities, addressing concerns, while maintaining focus on achieving the desired outcomes. Technical Deliverables, Oversight & Guidance Actively engage in technical solution discussions, leveraging your understanding of AI/ML, automation platforms, and full-stack development. Manage and provide technical direction to an AI/Automation Engineer, overseeing their work in developing tools (including GenAI components), and prototyping solutions in sandboxes. Identify automation opportunities through workflow analysis, user pain points, and feedback sessions Redesign and optimize manual or inefficient processes using a mix of AI, automation, and rules-based logic Develop and deploy automation tools, scripts, and GenAI components to streamline processes or decision-making Work in a sandbox environment to build and iterate MVPs before transitioning to production Collaborate with stakeholders to ensure alignment on goals, feasibility, and implementation timelines Document solutions clearly and guide teams toward adoption or handover Build APIs and backend services to integrate AI models with user-facing applications and internal platforms. Rapidly prototype AI-powered features and iterate based on feedback from users and stakeholders. Collaborate with cross-functional teams (e.g., data engineering, product, compliance) to operationalize AI use cases. Stay up to date with the latest AI/ML research, tools, and frameworks to continuously improve solution quality and speed of delivery. Requirements: Experience: Approximately 3 years in project management and technical coordination within a technology environment. Demonstrated ability to guide technical staff and engage in solutioning discussions. Technical Skills & Acumen: Solid understanding of AI/Automation Engineer responsibilities and technical stack, including: Low-Code AI/Workflow Automation platforms: Familiarity with platforms like Dify.ai, or similar platforms (e.g., UiPath, Automation Anywhere, Make) and a grasp of AI/ML concepts in automation. Demonstrate Proficiency in Python (automation, AI/ML integration) and familiarity with other scripting languages (JavaScript, PowerShell). Data Querying (SQL, NoSQL, APIs) and Dashboarding concepts (Tableau, QlikView). Dashboarding experience: Proven ability to create insightful and visually appealing dashboards using either Tableau or QlikView (or ideally both). Portfolio or detailed project descriptions are required. Experience with Python automation libraries (Selenium, Playwright, Airflow), workflow tools (Camunda, Power Automate), and AI/GenAI Stack (LLMs, OpenAI APIs, Hugging Face, LangChain, vector databases, RAG, prompt engineering, sandbox prototyping). Programming Languages & Frameworks Python (core automation, scripting, AI/ML integration) JavaScript/TypeScript (for tool UIs or web-based automation triggers) SQL (for querying, reporting, and workflow logic) Java or shell scripting for backend-heavy automation Automation & Workflow tools Python-based automation: Selenium, Playwright, Airflow, Pandas Experience building internal tools, bots, or custom workflow engines Workflow engines or low-code tools (e.g., Camunda, Power Automate, UiPath - even if you're building custom ones) AI / GenAI stack and Experience Experience with LLMs and tools such as OpenAI APIs, Hugging Face Transformers, LangChain, LlamaIndex, or other orchestration tools Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) Working knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), and integrating LLMs into practical workflows Experience deploying AI prototypes in internal sandbox environments Experience in working with sandbox/staging environments, especially for MVP/prototyping cycles Program Management & Soft Skills: Strong understanding of project management principles (Agile, Scrum). Excellent communication, analytical, and problem-solving skills. Ability to translate technical concepts for non-technical audiences and influence leadership. Proficient in project management software. Education: Bachelor's degree in computer science, Software Engineering, AI/ML, Data Science, or a related highly technical field, or equivalent practical engineering experience. -en