Backend Engineer – AI Solutions
Summary
Build and operate Python backend services powering ML and generative AI solutions (LLMs, RAG, vector DBs) on AWS, collaborating across product, security, and platform teams in Singapore.
About This Role
As a Backend Engineer, you will design, build, deploy, and operate secure backend services that enable AI, machine learning, and generative AI solutions for digital services. You will work closely with product, policy, data, cybersecurity, DevOps, and platform teams to translate operational needs into reliable, production-ready systems. You are a proactive, self-motivated, and resourceful team member with strong software engineering fundamentals, backend development experience, and an interest in applying backend engineering practices to AI-enabled products and platforms.
What You Will Be Working On
- Design, develop, and implement backend services that support machine learning, generative AI, and other intelligent digital services.
- Translate business, policy, and operational requirements into solution designs, technical specifications, and implementation plans.
- Build and maintain backend services for model pipelines, prompt workflows, retrieval-augmented generation solutions, APIs, integrations, and evaluation scripts.
- Conduct model and solution testing to assess accuracy, reliability, robustness, safety, bias, and fitness-for-purpose.
- Support the implementation of responsible AI controls, including guardrails, human oversight, audit logs, access controls, and explainability measures.
- Work with DevOps, cybersecurity, data, and platform teams to deploy AI solutions securely on approved enterprise environments.
- Support monitoring of deployed solutions for model drift, hallucination risks, performance degradation, operational errors, and security concerns.
- Assist in risk reviews, security compliance activities, vulnerability assessments, remediation tracking, and audit documentation.
- Provide technical support, troubleshooting, and optimisation for AI solutions across development, UAT, staging, and production environments.
What We Are Looking For
- Degree in Computer Science, Software Engineering, or a relevant IT field with 1–2 years of experience in AI engineering, machine learning engineering, data science, software engineering, or related technical roles.
- Hands-on experience developing backend services, APIs, integrations, or application components that support AI-enabled, enterprise, or digital services.
- Strong programming experience in Python, with familiarity in API development, testing, and commonly used AI / machine learning libraries or frameworks.
- Experience with large language models, prompt engineering, embeddings, vector databases, retrieval-augmented generation, or AI agent workflows.
- Good understanding of data preparation, model evaluation, MLOps / LLMOps, monitoring, logging, and production support practices.
- Understanding of responsible AI, AI governance, data protection, security, privacy, and risk management considerations.
- Experience with cloud environments such as AWS or other enterprise cloud platforms.
- Familiarity with CI/CD, DevSecOps, version control, testing, monitoring, logging, and operational support processes.
- Strong troubleshooting methodology and ability to resolve issues across data, model, application, integration, and infrastructure layers.
- Good communication and documentation skills, with the ability to explain technical concepts clearly to both technical and non-technical stakeholders.
Preferred Skills
- Experience implementing AI-enabled solutions in public sector, enterprise, or regulated industry environments.
- Familiarity with responsible AI frameworks, AI safety testing, model evaluation, red-teaming, and risk assessment approaches.
- Exposure to AWS AI/ML services, GitLab CI/CD, or similar secure delivery platforms.
- Knowledge of enterprise monitoring, log analytics, security monitoring, and automated evaluation pipelines.
- Experience working in collaborative environments and Agile development methodologies.
- Strong analytical thinking, systematic problem-solving, and the ability to manage multiple concurrent priorities.
What they ask for
Required
- Degree in CS/Software Engineering with 1–2 years experience in AI/ML engineering or related roles
- Hands-on backend services, APIs, and integrations experience for AI-enabled or enterprise services
- Strong Python programming with API development, testing, and AI/ML libraries/frameworks
- Experience with LLMs, prompt engineering, embeddings, vector databases, RAG, or AI agent workflows
- Understanding of data preparation, model evaluation, MLOps/LLMOps, monitoring, and production support
- Understanding of responsible AI, governance, data protection, security, privacy, and risk management
- Experience with cloud environments such as AWS
- Familiarity with CI/CD, DevSecOps, version control, testing, monitoring, and logging
- Strong troubleshooting across data, model, application, integration, and infrastructure layers
- Good communication and documentation skills
Preferred
- Experience implementing AI solutions in public sector, enterprise, or regulated industries
- Familiarity with responsible AI frameworks, AI safety testing, red-teaming, and risk assessment
- Exposure to AWS AI/ML services, GitLab CI/CD, or similar secure delivery platforms
- Knowledge of enterprise monitoring, log analytics, security monitoring, automated evaluation pipelines
- Experience in collaborative environments and Agile methodologies
- Strong analytical thinking and ability to manage multiple concurrent priorities