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MUFG-PMS Business Technology Services engineering team is seeking a talented AI Engineer to play a pivotal role in leveraging artificial intelligence to enhance our business operations.

The position is crucial for identifying opportunities where artificial intelligence can drive benefits across the MUFG-PMS business by creating AI augmented solution that align with the business domain and data architectures. This role will be responsible for developing applications and systems that utilize AI tools and Clouds AI services. As an AI Engineer you will work to develop and integrate innovative solutions to optimise and enhance business functionality and process. Working collaboratively with both the local executive team and with a global team dedicated to AI & Machine learning, this role will work at enterprise-wide to drive automation across the business-technology value chain; right from SDLC to BAU to create business value, build trust and protect the organisation from risk.

Key Accountabilities and main responsibilities

Strategic Focus

• Identify AI opportunities in collaboration with business stakeholders.
• Design & Build working Prototype/s for machine learning and AI applications.
• Develop and implement AI models and algorithms to optimize business processes and improve efficiency.
• Stay current with industry trends and best practices in AI technology and recommend innovative solutions to enhance business operations.

Operational Management

• Create business cases with clearly define objectives, work scope, and deliverables for AI projects.
• Assess and create technology use cases for AI Automation basis the business requirements.
• Partner with the Data team to define data requirements and ensure quality of Data for AI initiatives.
• Review and reinvent data to align as per the business scenarios.
• Monitor and analyse system performance, provide technical expertise and support to troubleshoot and resolve AI-related issues and performance bottlenecks.
• Analyse and interpret model outputs whilst continuing to refine models to achieve optimal results.
• Conduct thorough testing and validation of AI models to ensure accuracy and reliability.
• Document and communicate AI solutions and recommendations to technical and non-technical stakeholders clearly and effectively.
• Apply Subject matter expertise in Gen AI and Machine Language in Day to Day deliverables.
• Identify the design and development risk and work proactively to assess and mitigate.

People Leadership

• Collaborate with business analysts, and other stakeholders to understand requirements and deliver solutions.
• Work with DevOps and IT teams to ensure smooth deployment and operation of AI.
• Provide technical mentorship to junior developers and other team members.
• Work closely with security and compliance team to ensure that there is no security lapse in the design.

Governance & Risk

• Maintain Enterprise-wide governance to avoid compliance risks while ensuring the security of data and AI.
• Ensure to train the business data using generative AI with great security and responsibility to improve productivity and deliver competitive advantage.

The above list of key accountabilities is not an exhaustive list and may change from time-to-time based on business needs.

Experience & Personal Attributes

Experience

• Overall, 8-10 years of experience with minimum 5 years experience in building AI models using machine learning algorithms and deep learning.
• Proficiency in programming languages such as Java, Python, C++, R and Data Science.
• Experience on PySpark and other big data like Hadoop, Cassandra, etc.
• Understanding of machine language algorithms like linear regression, KNN, Na ve Bayes and Vector search.
• Strong understanding of API security standards and practices (e.g., OAuth, JWT).
• Familiarity with DevOps practices and CI/CD pipelines.
• Knowledge of database systems, both SQL and NoSQL.
• Exposure to AI platform using Python on CUDA platform and Hugging face repo to train the organisation data.
• Experience with any cloud platforms (PaaS and SaaS).
• Familiarity with microservices architecture and containerization (e.g., Docker, Kubernetes).
• Experience with Agile/Scrum development methodologies.

Personal Attributes

• Strong interpersonal skills to engage with people at all levels of the organization and build strong relationships and trust with clients and internal stakeholders.
• Highly effective communication, collaboration and influencing skills.
• Strong mentoring skills with a focus on coaching and developing teams.