Lead AI Infrastructure Engineer

Job description

Thoughtworks Singapore will be shortlisting applicants who have a current right to work in Singapore i.e. Singapore Citizens and Singapore Permanent Residents only.

At Thoughtworks, Lead AI Infrastructure Engineers design and maintain high-performance, scalable, and resilient infrastructure for modern AI workloads.

You’ll focus on enabling advanced inference systems, including LLMs, VLMs, and SLMs, across on-premises GPU clusters and cloud environments.

This role is critical to ensuring our clients’ AI systems achieve demanding requirements for throughput, latency, availability, and compliance.

As a senior technical leader, you will partner with ML engineers, platform engineers, AI researchers, and client stakeholders to deliver optimized infrastructure that is both robust and future-proof.

You will combine deep expertise in GPU-based inference infrastructure with a broader understanding of DevOps, agile delivery, and platform engineering to drive impactful AI solutions at enterprise scale.

Job responsibilities

• Design and operate GPU-based infrastructure (e.g., NVIDIA GB200, H100) across cloud and self-hosted environments.
  
  
• Architect scalable inference platforms that support real-time and batch serving with high availability, load balancing, and fault tolerance.
  
  
• Integrate inference workloads with orchestration frameworks such as Kubernetes, Slurm, and Ray, as well as observability stacks like Prometheus, Grafana, and OpenTelemetry.
  
  
• Automate infrastructure provisioning and deployment using Terraform, Helm, and CI/CD pipelines.
  
  
• Collaborate with ML engineers to co-design systems optimized for low-latency serving, continuous batching, and advanced inference optimization techniques (quantization, distillation, pruning, KV caching).
  
  
• Lead client engagements by shaping technical roadmaps that align AI infrastructure with business objectives, ensuring compliance, scalability, and performance.
  
  
• Champion DevOps and agile practices to accelerate delivery while maintaining reliability, quality, and resilience.
  
  
• Mentor and guide teams in best practices for AI infrastructure engineering, fostering a culture of technical excellence and innovation.
  
  

Job qualifications

Technical Skills

• Expertise in GPU-based infrastructure for AI (H100, GB200, or similar), including scaling across clusters.
  
  
• Strong knowledge of orchestration frameworks: Kubernetes, Ray, Slurm.
  
  
• Experience with inference-serving frameworks (vLLM, NVIDIA Triton, DeepSpeed).
  
  
• Proficiency in infrastructure automation (Terraform, Helm, CI/CD pipelines).
  
  
• Experience building resilient, high-throughput, low-latency systems for AI inference.Strong background in observability and monitoring: Prometheus, Grafana, OpenTelemetry.
  
  
• Familiarity with security, compliance, and governance concerns in AI infrastructure (data sovereignty, air-gapped deployments, audit logging).
  
  
• Solid understanding of DevOps, cloud-native architectures, and Infrastructure as Code.
  
  
• Exposure to multi-cloud and hybrid deployments (AWS, GCP, Azure, sovereign/private cloud).
  
  
• Experience with benchmarking and cost/performance tuning for AI systems.
  
  
• Background in MLOps or collaboration with ML teams on large-scale AI production systems.
  
  

Professional Skills

• Proven ability to partner with senior client stakeholders (CTO, CIO, COO) and translate technical strategy into business outcomes.
  
  
• Skilled at leading multi-disciplinary teams and building trust across diverse technical and business functions.
  
  
• Strong communication skills, with the ability to explain complex AI infrastructure concepts to both technical and non-technical audiences.
  
  
• Comfortable navigating uncertainty, making pragmatic decisions, and adapting quickly to evolving technologies.
  
  
• Passionate about creating scalable, sustainable, and high-impact solutions that help transform industries with AI.
  
  

Other things to know

Learning & Development

There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you.

But we also balance autonomy with the strength of our cultivation culture.

This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow.

We see value in helping each other be our best and that extends to empowering our employees in their career journeys.

About Thoughtworks

Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech.

As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work.

For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator.

Bring your brilliant expertise and commitment for continuous learning to Thoughtworks.

Together, let’s be extraordinary.

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