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Open nowPosted 13 days ago

Lead AI Engineer

MyCareersFuture94,028 open roles

Pay
SGD 8,000 – SGD 16,000 a month
Where
Central, Singapore
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Your applicationOpen nowLead AI EngineerMyCareersFuture · Central, Singapore

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on MyCareersFuture's own form.

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 13 days ago

The posting

We are looking for an experienced Lead AI Engineer to drive the design, development, and deployment of AI/ML-powered applications. Candidate should have strong hands-on experience in application development, lead and mentor a team of AI/ML developers, define best practices, and deliver scalable, production grade AI solutions aligned with business goals.

Key Responsibilities

  • Design, develop, and deploy AI/ML applications, microservices, and APIs on Kubernetes-based infrastructure, ensuring scalability, reliability, and performance across development, staging, and production environments.
  • Build and maintain end-to-end AI/ML pipelines covering deployment, monitoring, versioning, and continuous improvement using modern MLOps/AIOps tools and practices.
  • Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
  • Continuously evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
  • Collaborate closely with Business Analysts, Architect and technical teams to align AI engineering efforts with business objectives and ensure secure, compliant solutions.
  • Establish and maintain technical documentation, deployment runbooks and SOPs

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.
  • 8–10 years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
  • Expertise in Kubernetes – container orchestration, Helm charts, pod management, scaling, and troubleshooting.
  • Strong experience with MLOps/AIOps tools and practices (e.g., MLflow, Kubeflow, Airflow, model registries, monitoring frameworks).
  • Hands-on experience with cloud platforms – Azure, AWS, or GCP, including their AI services.
  • Strong programming skills in Python; familiarity with FastAPI, Flask, or similar frameworks is a plus.
  • Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
  • Lead and mentor development teams, drive delivery, and manage technical priorities.
  • Experience working with GenAI frameworks (e.g., LangChain), and vector databases.
  • Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry) for AI workloads.
  • Good understanding of AI security, responsible AI principles, and governance frameworks.
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