Gen AI Engineer

1 week ago


Singapore INCOME INSURANCE LIMITED Full time

Analytics Center of Excellence (COE) at Income Insurance is the enterprise team that champions and develops AI/ML solutions. We focus on in‐house solution development as well as partnerships. To ensure the successful execution of Income's enterprise strategy to build Analytics as a product through impactful AI/ML solutions, driving innovation, and cultivating AI culture, we are seeking a highly skilled and experienced Gen AI Engineer to join our team. The selected candidate will focus on building Generative AI‐based solutions, with a particular emphasis on Microsoft Copilot Studio. Responsibilities Take ownership of AI/ML use cases, from design and implementation to continuous enhancement. Act as a technical specialist in AI, primarily focusing on Generative AI. Design and develop solutions to address various business challenges, particularly those related to optimizing operational efficiency. Collaborate with other data engineers, analysts, data scientists, product specialists, and stakeholders to build well‐crafted, pragmatic, and robust solutions that meet business requirements. Stakeholder management and engagement: proactively engage with stakeholders to understand their needs and translate them into technical requirements for AI/ML modeling. Maintain documentation of dataset curation, modeling approach, model performance, code changes, and workflows. Demonstrate a strong understanding of data privacy regulations such as PDPA, and AI governance guidelines to ensure compliance. Foster an innovative and growth‐oriented mindset, continuously seeking opportunities to enhance AI/ML models and drive improvements across the organization. Requirements At least 3–5 years of experience in a data science role, with relevant experience in AWS platform and/or Microsoft Copilot Studio. Bachelor's degree in computer science or equivalent. Familiarity with techniques for Document Chunking, Embedding, and Information Retrieval for improving model accuracy and relevance. Expertise in Prompt Engineering for designing and managing effective prompts. Hands‐on experience with AWS Bedrock and Microsoft Copilot Studio, including deploying solutions using foundation models and integrating them into scalable applications using APIs and orchestration tools. Experience in Agentic Flow for maximizing the utility of models, including understanding user intent and context to drive meaningful interactions. In‐depth knowledge of supervised and unsupervised ML models – linear & logistic regression, clustering, tree‐based models like random forest, bagging, and boosting models. Proficient in SQL, Python, and Spark. Proven experience in implementing MLOps practices on AWS. Familiar with Data Warehouses such as Redshift, Hive, and S3. Passionate about technology and always looking to upskill based on new developments in the AI space. AWS or Microsoft certifications will be a plus. Experience in the financial industry, telecommunications, or consulting is preferred. #J-18808-Ljbffr



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