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Firmus Technologies

Designs and operates AI GPU data-centers.

Engineering Manager - Software, AI Cloud

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • A bachelor's degree in computer science or a related technical field is required.
  • At least 4 years of experience managing engineers, with direct ownership of hiring, growth, and performance for a team of at least 8 engineers.
  • Track record building high-performing, self-improving engineering teams and a strong delivery culture.
  • Proven track record delivering complex software at scale and making delivery predictable across multiple teams and dependencies.
  • Ability to make sound decisions with incomplete information in a fast-paced, high-growth environment and reprioritize as business requirements change.
  • Experience with AI-assisted development and agentic AI, and ability to improve team throughput and quality using these tools.
  • At least 10 years in software engineering, including a strong hands-on background as a senior or staff engineer before moving into management, with the ability to reason deeply about architecture and remain close to the technology.
  • Deep experience designing and operating customer-facing APIs and control-plane services in production, including API contracts such as OpenAPI or gRPC, versioning, and the SDKs, CLI, or infrastructure-as-code providers built on top.
  • Experience building multi-tenant, secure-by-default software at scale, including identity and authorization, tenancy isolation, API gateways and rate limiting, and billing or metering.
  • Fluency in a modern backend stack such as Go or Python, on a cloud-native foundation including Kubernetes, infrastructure-as-code, and CI/CD, with the technical depth to contribute to design reviews and make sound technical trade-offs.
  • Experience delivering customer-facing web applications using React or a similar framework, including API-to-UI contracts for an integrated console experience.
  • Comfort reviewing code and maintaining a high bar in design and code review.
  • Experience owning operational excellence for production systems, including reliability and SLOs, on-call and incident management, and change control.
  • Experience owning security and compliance for production systems.
  • Comfort owning the path to production for AI or agentic workloads, including review and security gates for AI-assisted development.
  • Ownership of infrastructure, platform, or software costs as part of running a team, and judgment to balance costs against reliability and speed.
  • Willingness to participate in the incident-response on-call rotation for the team's services.
  • Willingness to travel overseas occasionally when required.
  • Ability to partner with product, present to senior technical leadership, and brief enterprise or government customers on technical trade-offs.
  • Ability to connect engineering investment to business outcomes by weighing customer value, cost, risk, and platform scalability when setting priorities.
  • Clear and effective written and verbal communication in English, including explaining delivery or architectural trade-offs to a CTO or customer while preserving the substance.

Responsibilities

  • Lead the squads as their Single-Threaded Owner; engineers and tech leads report to the role, which works alongside product, architecture, and delivery peers.
  • Hire engineers, develop them through coaching and clear feedback, and manage their performance directly.
  • Own organizational design, headcount planning, and engineering culture for the group.
  • Own end-to-end delivery for the team, translating the product roadmap into sequenced, predictable delivery and shaping prioritization with product.
  • Work with tech leads on sprint planning and release gates; own cross-squad dependencies, make delivery health visible through metrics, and balance velocity against reliability and technical debt.
  • Set the engineering quality bar and drive cross-cutting decisions to completion, including build-versus-buy-versus-open-source choices, API and control-plane design, customer-facing contracts, and product SLAs.
  • Maintain rigorous design and code review, unblock difficult problems, and champion AI-assisted development while maintaining design, review, and security standards.
  • Own the reliability and security of the software the squads run in production.
  • Serve as the escalation point above the operations centre and own L3 incident resolution, SLA-breach response, and post-mortems that lead to runbook and prevention work.
  • Set standards for SLOs, on-call, and change management.
  • Govern how AI-generated code and agentic workloads reach production, extend existing SOC 2 Type 2 and ISO 27001 controls as the product expands into new regions, and own cost efficiency while balancing reliability, performance, and speed against infrastructure spend.
  • Represent the team to engineering leadership and the CTO, communicating progress, risks, and needed decisions.
  • Lead customer technical briefings and represent engineering when escalations involve delivery, reliability, or product architecture.
  • Align with product, architects, delivery, and operations so the product ships and runs as one system.
  • Build and operate the customer-facing software of the Firmus AI Cloud, including public APIs, the control plane, web console, SDKs, CLI, and Terraform provider, enabling customers to provision and run GPU compute quickly and reliably.
  • Operate these capabilities as products, investing in engineer experience, reliability, and a low-friction customer self-service journey.
  • Build the team to scale the AI Cloud toward gigawatt-scale AI factories across regions and expand the role's scope as earned.

Desired Qualifications

  • Experience owning security and compliance for production systems against frameworks such as SOC 2 Type 2 or ISO 27001.

About the Company

Firmus Technologies

Designs and operates AI GPU data-centers.

Firmus Technologies builds AI-focused data centers called the AI factory, featuring liquid-cooled GPU campuses and a GPU cloud. Its AI FactoryOS ties cooling, racks, and chips together to maximize uptime and throughput. It differentiates with a full hardware–software stack for AI, MLPerf efficiency data, NVIDIA partnerships, and renewable-powered campuses such as Tasmania’s Green AI Factory Zone. Its goal is to scale energy-efficient, sovereign AI infrastructure for tens of thousands of GPUs while reducing costs and boosting AI throughput.

Company size
51-200
Company stage
IPO
Headquarters
Launceston, Australia
Founded
2019

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