Associate AI Engineer

About Singlife

Singlife is a prominent homegrown financial services company dedicated to offering consumers enhanced financial freedom. Leveraging innovative technology and a broad portfolio of products and services, Singlife empowers individuals to manage their financial wellbeing throughout various life stages.

The company provides a full spectrum of insurance plans, employee benefits, partnerships with financial advisory networks and bancassurance. Additionally, it offers investment advisory solutions via the GROW with Singlife platform, and the mobile-centric Singlife Account, which is an insurance savings product.

Singlife holds exclusive insurance provider status for the Ministry of Defence, Ministry of Home Affairs, and Public Officers Group Insurance Scheme. It is also a committed signatory to the United Nations Principles for Sustainable Insurance and the Principles for Responsible Investment, underlining its sustainability focus.

The merger of Aviva Singapore and Singlife in September 2020 created one of Singapore's largest homegrown financial firms in a S$3.2 billion transaction, the biggest insurance deal in Singapore then. In March 2024, Singlife was acquired by Sumitomo Life, one of Japan’s key life insurers, in a deal valued at S$4.6 billion, marking one of Southeast Asia's largest insurance deals.

Role Overview

The Associate AI Engineer is an entry-level role within Singlife's AI Platform Engineering team. This position involves building, testing, and maintaining AI-driven solutions on the AWS cloud platform.

As part of the AI Centre of Excellence, the role contributes to delivering Generative AI, Agentic AI, and Document Intelligence capabilities while adhering to engineering standards, security protocols, and governance policies.

You will gain direct experience with AWS technologies including Amazon Bedrock, AgentCore, OpenSearch, Textract, Lambda, and API Gateway to develop practical AI applications and solutions.

Key Responsibilities

• Develop AI applications, APIs, and reusable components utilizing AWS AI and cloud-native technologies.
• Implement Generative AI functions such as prompt-driven applications, retrieval-based solutions, and automation of AI workflows.
• Support the creation of Retrieval-Augmented Generation (RAG) solutions incorporating enterprise knowledge bases.
• Design document processing workflows employing OCR and document intelligence tools.
• Integrate AI solutions with enterprise API systems and business applications.
• Create and maintain Python-based services adhering to engineering best practices and standards.
• Employ AWS AI services like Bedrock, AgentCore, Textract, Comprehend, OpenSearch, and Lambda for building components within architectural designs.
• Facilitate connections from AI outputs to enterprise REST APIs and downstream systems, managing data transformation and outcome validation.
• Follow AWS tagging conventions and manage cost implications related to AI solutions.
• Work collaboratively with Cloud Engineering teams to ensure that AI solutions are secure, scalable, and dependable.
• Contribute software components and utilities to a shared AI technology library, ensuring code is clean and reusable.
• Document every component thoroughly with function docstrings, README files, and usage demonstrations.
• Engage actively in code reviews, accepting and applying feedback constructively.
• Implement AI engineering controls including handling of personally identifiable information (PII), output checks, content filtering, and audit logging.
• Keep current with advancements in Generative AI, Agentic AI, and AWS AI services.
• Participate in technical discussions, design meetings, and knowledge-exchange sessions.
• Propose ideas that boost engineering efficiency and solution quality.
• Pursue relevant AWS and AI certifications to foster professional growth.

Candidate Requirements

• Possess 2 to 3 years of professional or significant project/internship experience in software or AI engineering, particularly in AI/ML system development.
• Proficient in Python programming capable of producing clean, structured, and testable code independently.
• Experience with AWS cloud services, including any combination of Lambda, S3, API Gateway, or AI-specific services such as Bedrock, AgentCore, Textract, or SageMaker.
• Sound understanding of REST API creation and consumption using frameworks like FastAPI or Flask.
• Practical knowledge of Generative AI concepts including large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering, embeddings, and vector storage.
• Good version control practices using Git, including branching, pull requests, and participating in code reviews.
• A genuine interest and proactive engagement in building AI applications beyond theoretical knowledge.
• Experience working specifically with AWS Bedrock for model invocation and prompt engineering via APIs.
• Familiarity with document processing pipelines such as PDF extraction and OCR to obtain structured data from unstructured sources.
• Exposure to vector databases or semantic search technologies such as Pinecone, OpenSearch, or pgvector.
• Possession of AWS Cloud Practitioner or AWS Developer Associate certification, or actively pursuing these certifications.
• Experience participating in team environments emphasizing code reviews, CI/CD pipelines, and disciplined documentation.
• Experience or exposure to financial services or regulated data environments is advantageous.