Lead AI Engineer

hewlett packard enterprise singapore pte. ltd.; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Hewlett Packard Enterprise Singapore Pte. Ltd. is seeking an experienced Lead AI Engineer to guide the design, development, and deployment of AI/ML powered applications on Kubernetes-based infrastructure.

You will mentor a team of AI/ML engineers, define best practices, and drive scalable, production-grade AI solutions aligned with business goals. Strong expertise in MLOps, cloud platforms, and observability is required.

Qualifications

• Bachelor's or Master's degree in CS, Engineering, AI/ML, or related field.
• 8–10 years hands-on software engineering with AI/ML deployment
• Kubernetes: orchestration, Helm, pod management, scaling, troubleshooting
• MLOps/AIOps tools: MLflow, Kubeflow, Airflow, model registries, monitoring
• Cloud platforms: Azure, AWS, or GCP and their AI services
• Strong Python programming; FastAPI/Flask familiarity
• CI/CD pipelines and GitOps with Docker, Jenkins, or GitHub Actions
• Lead and mentor development teams; deliver results
• GenAI frameworks (LangChain) and vector databases
• Observability/monitoring: Prometheus, Grafana, OpenTelemetry
• AI security, responsible AI, governance frameworks

Responsibilities

• Design, develop, and deploy AI/ML applications, microservices, and APIs on Kubernetes-based infrastructure.
• Build end-to-end AI/ML pipelines with deployment, monitoring, versioning, and CI/CD.
• Lead and mentor AI/ML engineers; conduct code reviews and establish best practices.
• Evaluate emerging AI tools, LangChain, GenAI frameworks, and vector databases.
• Collaborate with Analysts, Architects, and teams to align AI work with business goals and security.
• Create and maintain technical docs, deployment runbooks, and SOPs

Skills

AI/ML development

Kubernetes

Python

MLOps

CI/CD

Cloud platforms

Leadership

GenAI frameworks

Observability

AI governance

Education

Bachelor's/Master's in CS/Engineering/AI

Tools

Kubectl

Helm

MLflow

Kubeflow

Airflow

Prometheus

Grafana

OpenTelemetry

GitHub Actions

Docker

Job description

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.