Backend Engineer (AI MLOps)

Location: Singapore

Company

hirify.global is a development company established in 2010 that delivers mobile, web, and enterprise applications for global clients across IoT, blockchain, banking, fintech, networking, and ecommerce.

What you will do

• Implement AI governance controls and ensure compliance with data security, privacy, Responsible AI, ICT&SS, IM8, SSP, and PDPA requirements.
• Build monitoring, observability, audit logging, dashboards, alerts, and incident response procedures for AI models and agents.
• Develop model and agent evaluation processes covering test datasets, benchmarking, regression testing, human review, task success, tool-use correctness, and trajectory analysis.
• Configure AI safety and security guardrails, including content filtering, PII detection and redaction, prompt-injection protection, tool allow-lists, action limits, approvals, emergency stops, and spend controls.
• Run red-teaming and security testing for agentic AI threats and track remediation.
• Build MLOps pipelines for model and prompt versioning, deployment, rollback, and lifecycle management while collaborating with platform, AI/ML, DevSecOps, backend, and architecture teams.

Requirements

• Degree or Diploma in Computer Science, Data Science, Information Technology, or a related discipline.
• At least 2 years of relevant experience in software engineering, MLOps, DevOps, data engineering, or AI operations.
• Good Python programming skills and working knowledge of JavaScript or TypeScript for dashboards and web tools.
• Experience with model monitoring, evaluation, or observability tools such as Amazon CloudWatch, SageMaker Model Monitor, MLflow, Langfuse, or equivalent.
• Understanding of LLM evaluation techniques, including groundedness, faithfulness, LLM-as-judge, and red-teaming; familiarity with Amazon Bedrock Guardrails, Model Evaluation, and model invocation logging.
• Understanding of agentic AI risks and controls, including excessive agency, prompt injection, tool misuse, human-in-the-loop design, agent evaluation, and tracing tools such as Langfuse or OpenTelemetry.
• Experience with CI/CD pipelines and version control systems such as Git; knowledge of Docker and Kubernetes.
• Good understanding of data security, privacy, and Responsible AI principles.
• Understanding of Government ICT&SS management policies, IM8, SSP requirements, and observability practices applied to AI guardrails, audit logging, and monitoring.
• Strong attention to detail, a risk-aware and quality-driven mindset, Agile experience, and strong collaboration, communication, and documentation skills.

Nice to have

• Familiarity with Singapore’s Model AI Governance Framework, AI Verify, IM8, and PDPA.
• Experience with Government Commercial Cloud or security assessments for government projects.
• AWS certifications such as Machine Learning Engineer Associate, AI Practitioner, or Cloud Practitioner.

Culture & Benefits

• 14 days of annual leave, with up to 6 unused days carried forward.
• Paid sick leave, hospitalization leave of up to 60 days, and paid public holidays with time off in lieu when applicable.
• Group medical insurance covering outpatient and hospitalization, plus marriage, newborn, and bereavement allowances.
• Work equipment, mentorship, direct coaching from senior management, and skill development through client projects, workshops, and seminars.
• Clear progression toward leadership roles, with complimentary snacks and drinks in the office.