What is this position about?
The AI Solutions division within Wealth Management IT drives the adoption and industrialization of Artificial Intelligence across Wealth Management IT, with a specific focus on delivering secure, governed and value-driven AI capabilities for IT teams.
The AI for IT squad focuses on embedding AI into the daily work of IT teams in order to improve software delivery, operational resilience, cyber risk management and engineering productivity. The ambition is to progressively move from isolated assistants and copilots toward governed AI capabilities directly embedded into IT processes across three core domains: Build, Run and Secure.
We are looking for a hands-on and highly motivated Data Scientist / AI Expert to join the AI for IT squad in Singapore.
The role will contribute to the design, evaluation, prototyping, implementation and industrialization of AI solutions dedicated to IT transformation. The candidate will work on strategic AI for IT initiatives covering developer productivity, AI-assisted production operations, vulnerability analysis and remediation, and the continued evolution of specialized AI assistants and agents deployed within the Wealth Management IT ecosystem.
The ideal candidate combines strong data science and AI engineering skills with a pragmatic delivery mindset. The role is not limited to research or experimentation: the objective is to build concrete, secure and usable AI solutions that can be adopted by IT teams in their day-to-day activities.
What would be your typical day at BNPP Paribas look like?
Primary Role Responsibilities
• Contribute to the AI for IT roadmap across the three strategic domains: Build, Run and Secure.
• Analyse, evaluate and recommend AI-powered development tools for IT teams, including Vibe Coding and AI coding environments such as Cursor, Kline / Cline-style tools, AI4Dev, DevX or similar solutions.
• Assess how AI coding assistants can improve software engineering activities such as code generation, code review, unit testing, documentation, refactoring, knowledge reuse and developer onboarding.
• Design and prototype AI-assisted SDLC use cases, including coding assistants, test generation, documentation assistants, development workflow automation and knowledge retrieval across engineering repositories.
• Contribute to AIOps initiatives aimed at supporting production teams through AI-assisted monitoring, alert triage, incident diagnosis, root cause analysis, runbook recommendation and runbook execution support.
• Work with production, support and application teams to identify operational pain points where AI can reduce alert noise, accelerate diagnosis, standardise response procedures and improve incident resolution efficiency.
• Lead or contribute to AI initiatives focused on cybersecurity and vulnerability management, including vulnerability analysis, prioritisation, remediation recommendation, exposure reduction and cyber backlog optimisation.
• Design AI-assisted approaches to help teams anticipate, analyse and remediate vulnerabilities faster, while ensuring that security decisions remain governed, traceable and validated by the appropriate owners.
• Continue to enhance and industrialize existing GenAI initiatives around specialized chatbots and agents, including application management assistants, support assistants, governance assistants, workplace assistants and administrative support assistants.
• Contribute to the evolution of the WM GENIX platform and related AI spaces, including specialized assistants connected to knowledge sources such as SharePoint and Confluence, with future integrations expected around Jira, ServiceNow, Clarity and Microsoft 365 services.
• Build and maintain Retrieval-Augmented Generation capabilities, prompt patterns, evaluation datasets, knowledge base structures and AI workflows to improve the quality, reliability and adoption of AI assistants.
• Develop proof-of-concepts and prototypes to evaluate emerging AI frameworks, LLM capabilities, agentic architectures, MCP-based integrations, tool calling patterns and automation opportunities.
• Translate IT pain points and strategic objectives into practical AI use cases, technical specifications, user stories, evaluation criteria and measurable outcomes.
• Ensure that AI solutions are designed with appropriate governance, security, data privacy, auditability, cost control and human oversight principles.
• Define and monitor KPIs to measure value creation, including productivity gains, adoption, quality improvement, operational efficiency, incident resolution improvement, cyber remediation acceleration and user satisfaction.
Contributing Responsibilities
• Support the AI for IT Product Owner and AI Solutions management in shaping the AI for IT execution roadmap and prioritizing initiatives based on value, feasibility, risk and readiness.
• Provide technical analysis and recommendations on third-party AI tools, open-source frameworks, enterprise AI platforms and vendor solutions.
• Collaborate with Group AI, IT, cybersecurity, architecture and production stakeholders to ensure alignment with enterprise standards and approved AI capabilities.
• Contribute to governance documentation, technical assessments, risk reviews and decision materials required to move AI use cases from prototype to production.
• Participate in knowledge sharing, internal demos, communities of practice and upskilling initiatives around GenAI, AI agents, AI-assisted development, AIOps and AI for cybersecurity.
• Promote responsible AI adoption by ensuring explainability, traceability, human accountability and controlled usage of AI capabilities.
• Mentor junior profiles or interns contributing to AI for IT initiatives and help structure their technical work.
What is required for you to succeed?
The candidate should demonstrate a combination of strong AI / data science expertise, software engineering culture, enterprise integration experience and excellent communication skills. He/she must have a genuine willingness to deliver practical AI solutions in a governed banking environment.
• Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics or a related field.
• Minimum 5 years of experience in data science, AI engineering, software engineering or related technology roles.
• Proven hands-on experience delivering AI, GenAI, data science or automation solutions.
• Experience in an enterprise IT environment is required; experience in banking, financial services or another regulated industry is a strong advantage.
• Experience with AI solutions supporting IT teams, developer productivity, production support, cybersecurity or knowledge management would be a strong differentiator.
• Good to have: experience with AI coding tools such as Cursor, Kline / Cline-style agents, GitHub Copilot, AI4Dev, DevX or similar developer assistants.
• Good to have: experience integrating AI solutions with Confluence, Jira, ServiceNow, SharePoint, Microsoft 365 or ITSM / ITOM platforms.
• Good to have: Azure AI, cloud, cybersecurity or data science certifications.
Technical Skills
• Strong hands-on experience in Python and modern data science / AI engineering practices.
• Solid understanding of Generative AI, Large Language Models, prompt engineering, RAG, embeddings, vector databases, tool calling and agentic AI patterns.
• Experience designing or integrating AI assistants, chatbots, copilots or AI agents in enterprise environments.
• Good knowledge of software engineering workflows and SDLC activities, including coding, testing, code review, CI/CD, documentation and release processes.
• Experience with AI coding assistants, developer productivity tools or AI-assisted software engineering solutions.
• Understanding of AIOps concepts such as monitoring, alert correlation, incident triage, root cause analysis, runbook automation and production support processes.
• Understanding of cybersecurity and vulnerability management concepts, including vulnerability triage, prioritisation, remediation workflows and risk-based decision-making.
• Experience working with APIs, integration layers, data pipelines and enterprise knowledge sources.
• Knowledge of RAG implementation patterns using structured and unstructured data sources such as SharePoint, Confluence, Jira, ServiceNow or similar platforms.
• Knowledge of cloud, containerization and deployment concepts such as Docker, Kubernetes, CI/CD pipelines and private cloud environments.
Behavioral Skills
• Strong analytical mindset and ability to structure complex problems into actionable AI use cases.
• Pragmatic delivery mindset, with the ability to move from exploration to concrete implementation
• Curiosity and strong interest in emerging AI technologies, especially AI agents, AI coding, AIOps and enterprise GenAI platforms.
• Strong communication skills, with the ability to explain technical AI concepts to IT, security, production and management stakeholders.
• Autonomy, ownership and ability to drive topics from analysis to prototype and industrialization.
• Strong sense of accountability, particularly around security, governance, data protection and responsible AI adoption.
About BNP PARIBAS
As the leading European Union bank, and one of the world’s largest financial institutions with an uninterrupted presence in the region since 1860, BNP Paribas offers a wide range of financial services for corporate, institutional and private investors spanning corporate and institutional banking, wealth management, asset management and insurance.
We passionately embrace diversity and are committed to fostering an inclusive workplace where all employees are valued and encourage applicants of all backgrounds, including diversity of origin, age, gender, sexual orientation, gender identity, religion applicants who may be living with a disability. We have a number of internal employee networks in place to empower our staff to act and challenge the status quo.
• BNP Paribas PRIDE is highly active in favour of the LGBTQIA+ community
• BNP Paribas MixCity which fosters better representation of women at all levels of the organization
• Ability, the mutual aid network for employees with a disability or a disabling or chronic illness
• BNP Paribas CulturAll which celebrates diverse backgrounds
BNP is committed to financing a carbon-neutral economy by 2050. The Group is a founding member of the Net-Zero Banking Alliance and has set up its own Low Carbon Transition Group to support its clients through their energy transitions.
https://careers.apac.bnpparibas/
More information
BNP Paribas - Diversity & Inclusion Journey
BNP Paribas - The Bank Of Green Changes
Award Obtained
BNPP has won Top employer Europe award in a 10th consecutive year
