Forward Deployed Architect

SARAWAK ARTIFICIAL INTELLIGENCE CENTRE SDN BHD; Kuching; On-site; MYR 250,000 - 500,000; Full time

Job summary

SARAWAK ARTIFICIAL INTELLIGENCE CENTRE SDN BHD is seeking a Lead AI Architect to design end-to-end production-quality agentic AI systems. You will establish reference architectures, drive complex multi-team initiatives, and enforce security, guardrails, and policy compliance across runtimes.

Responsibilities include leading architecture reviews, shaping engineering standards, and guiding collaborations with AI scientists to continuously improve agent quality via telemetry and evaluation

Qualifications

• Masters/PhD in Computer Science, AI or ML with 5+ years in AI-focused role.
• Ability to lead complex, multi-workstream AI or software programmes with architecture ownership.
• Experience designing high-throughput, low-latency systems across software and hardware.
• Security, guardrails, auditability and policy enforcement in agent runtimes.

Responsibilities

• Design production-quality architecture for agentic AI systems end to end.
• Set reference architectures and engineering standards for lead engineers.
• Architect data flywheels with AI Scientists to improve agent quality.
• Embed security and auditability into agent runtimes.
• Drive build-versus-use decisions on OSS and third-party platforms.
• Lead strategic AI programmes across teams and sites.
• Negotiate customer AI requirements and manage vendor partnerships.

Skills

C++

Python

CUDA

Kubernetes

Education

Master’s/PhD in Computer Science/AI/ML

Tools

Kubernetes

Job description

SARAWAK ARTIFICIAL INTELLIGENCE CENTRE SDN BHD View all jobs

Design the solution architecture for production-quality agentic AI systems end to end: Kubernetes deployment, agent runtimes, memory systems, orchestration, tool integration, and evaluation pipelines

Set the reference architectures and engineering standards that Lead engineers build against, and hold the line on them through architecture review

Architect data flywheels with AI Scientists that continuously improve agent quality through telemetry, benchmarking, automated evaluation, and structured feedback loops

Embed security, guardrails, sandbox isolation, auditability, and policy enforcement directly into agent runtimes

Drive disciplined build-versus-use decisions on open-source and third-party agent platforms

Lead strategic AI programmes spanning several teams or functions and coordinate organisation-wide adoption across sites and business units

Negotiate customer AI requirements, own key vendor and research partnerships, and grow Lead engineers into architecture and programme ownership

Set the applied research agenda jointly with our AI Engineers, publish at least one Q1/Q2 journal paper each year, and represent SAIC as a technical voice externally.

What You Will Bring

Strong programming skills in C++, Python, and CUDA or another GPU programming model, with a track record of production-quality, performance-critical software

Proven experience designing and optimising high-throughput, low-latency systems, reasoning across software stacks, hardware capabilities, and system bottlenecks

Deep HPC and AI infrastructure knowledge: benchmarking on large-scale clusters, GPUs, InfiniBand and Ethernet, RDMA, Kubernetes, and distributed storage

Track record leading complex, multi-workstream AI or software programmes with accountability for architecture, schedule, and technical risk

Recognised depth in two or more AI domains, with demonstrated ability to set engineering standards and grow Lead-level engineers

Agile delivery leadership at programme level, including the ability to operate in a Scrum Master capacity and align multiple teams to a common plan

Credibility with senior client and partner stakeholders, and the ability to influence a technical decision you do not control

Qualifications

Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field, with more than five (5) years in an AI-focused role and demonstrated ability to lead projects and mentor team members.

Nice to Have

Experience in regulated industries including but limited to government, finance, or healthcare; background in AI policy, cybersecurity, and compliance frameworks; patents, standards body participation, or conference programme committee service; experience building an engineering practice or function from an early stage; established working relationships with platform and hardware vendors or with academic research groups.

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