Expert, AI Engineer (Techcom Insurance)

Job Purpose
Lead the design, development, deployment, and optimization of AI-powered solutions that deliver business value across Techcom Insurance. The role is responsible for transforming AI use cases from experimentation into scalable production systems, leveraging Generative AI, Large Language Models (LLMs), Machine Learning, AI Agents, and cloud-native technologies. The position also drives AI adoption, solution architecture, governance, and best practices while mentoring engineers and collaborating closely with business and technology stakeholders.
Key Accountabilities (1)
AI Solution Design & Development
Design, develop, and deploy AI solutions using Machine Learning, Generative AI, LLMs, and Agentic AI frameworks.
Build intelligent applications such as copilots, chatbots, recommendation engines, document processing solutions, and AI assistants.
Develop Retrieval-Augmented Generation (RAG) solutions integrating enterprise data sources and knowledge bases.
Collaborate with business teams to identify AI opportunities and translate business requirements into technical solutions.
Evaluate AI model performance and continuously improve solution effectiveness against business KPIs.
Key Accountabilities (2)
AI Platform & Engineering Excellence
Develop scalable and secure AI architectures on cloud platforms such as AWS, Azure, or GCP.
Build and optimize AI pipelines covering model development, prompt engineering, evaluation, deployment, monitoring, and lifecycle management.
Implement MLOps and LLMOps practices, including CI/CD, model versioning, testing, observability, and rollback mechanisms.
Ensure AI solutions meet performance, reliability, security, and compliance requirements.
Collaborate with Data Engineers and Platform Engineers to integrate AI services into enterprise systems.
AI Governance & Innovation
Establish best practices for responsible AI, model governance, and AI risk management.
Evaluate emerging AI technologies, frameworks, and tools to drive innovation.
Support the adoption of AI standards, security controls, and data governance requirements.
Drive continuous experimentation and rapid prototyping of new AI capabilities.
Key Accountabilities (3)
Project & Stakeholder Management
Lead AI initiatives from concept through production deployment.
Manage project priorities, timelines, risks, and stakeholder expectations.
Partner with business, product, architecture, security, and engineering teams to ensure successful AI implementation.
Provide technical leadership and strategic recommendations related to AI adoption and transformation.
Talent Development
Mentor and coach AI Engineers, Machine Learning Engineers, and Data Scientists.
Promote engineering best practices, knowledge sharing, and continuous learning.
Contribute to building AI capabilities and technical expertise across the organization.
Key Relationships - Direct Manager
Director, Data Science
Key Relationships - Direct Reports
Director, Data Science
Key Relationships - Internal Stakeholders
Director, Data Science
Key Relationships - External Stakeholders
Director, Data Science
Success Profile - Qualification and Experiences
Qualifications
- Master's degree (or higher) in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering, Information Technology or other Numerical Disciplines
Work Experience
- 10+ years of relevant experience in areas of data analysis, machine learning, deep learning model development on large amount of data, implementing and deploying various statistical models
- English proficiency requirements are pursuant to Techcombank's policy
- Deep experience in querying databases and coding (e.g. Python, R, Spark, Scala, SQL, Java, C, C++)
- Extensive experience in building data and analytics solutions and products, data mining and statistical analysis
- Experience in application of machine learning and AI to questions related to the financial markets
- Strategic decision taking and thinking, able to deal with very senior management, translate tech to business and vice versa
- Deep experience in Agile Software Development and has mastery of Agile principles, practices and Scrum methodologies
- Management experience, leading projects in the past, building and mentoring scientists, leading them towards success