Role Description Lightning AI is looking to hire a Platform Support Engineer to join our APAC Customer Experience team, supporting ML engineers running large-scale training and inference workloads across cloud infrastructure, Kubernetes, and GPU platforms in production environments. This role is not a ticket router or traditional support engineer. You are a technical partner to ML teams - helping diagnose failures, improve reliability, and guide customers through complex distributed systems problems. The problems range from Kubernetes scheduling and GPU orchestration to distributed PyTorch failures, inference latency, networking bottlenecks, storage performance, and platform reliability. You’ll gain exposure to a wide variety of real world AI workloads across industries and help shape the infrastructure powering the next generation of ML applications. This role is remote and open to candidates based in either the Philippines or Singapore. The role follows a Thursday–Sunday schedule, with working hours from 7:00 AM to 5:00 PM local time (UTC+8). What You'll Do - Work Directly With ML Engineers - Partner directly with customer engineering teams running training and inference workloads in production - Help customers diagnose and resolve complex distributed systems and ML infrastructure issues - Act as a technical advisor during high impact incidents and platform degradation events - Translate infrastructure level issues into actionable guidance for ML engineers - Build credibility with customers through strong technical reasoning and clear communication - Debug ML Infrastructure & Distributed Workloads - Investigate failures involving distributed training, Kubernetes orchestration, GPU allocation, networking, and storage systems - Troubleshoot PyTorch, CUDA, NCCL, and inference serving related issues - Analyze logs, metrics, traces, and system behavior to isolate root causes - Debug containerized workloads running across Kubernetes and bare metal GPU environments - Support customers scaling workloads across multi node GPU systems - Diagnose performance bottlenecks involving compute, memory, networking, or storage - Improve Reliability & Platform Operations - Identify recurring patterns across customer issues and drive long term reliability improvements - Contribute to post incident reviews and operational improvements - Build internal tooling, automation, documentation, and runbooks - Partner closely with infrastructure, networking, and platform engineering teams - Help improve observability, operational visibility, and troubleshooting workflows - Improve the customer experience through better processes and technical guidance What This Role Is Not - This is not a traditional help desk or ticket routing support role - This is not purely customer success or account management - This is not a backend engineering role - This is not a passive escalation position - This role is for engineers who enjoy solving difficult technical problems while working closely with other engineers. Qualifications - Strong software engineering and systems troubleshooting background - Experience with Kubernetes and containerized environments - Linux systems knowledge, including networking, storage, process management, and performance tuning - Experience with cloud infrastructure and distributed systems - Experience with observability and debugging tools such as Prometheus, Grafana, or OpenTelemetry - Hands on experience operating machine learning workloads in production or research environments - Experience with distributed ML systems and tooling such as PyTorch, CUDA, or NCCL - Familiarity with GPU infrastructure and orchestration - Experience troubleshooting performance, reliability, or scaling issues in ML infrastructure - Understanding of the operational challenges involved in running ML systems at scale - Strong communication skills and ability to work directly with highly technical customers and engineering teams - Comfortable operating in fast moving, highly ambiguous environments - Enjoys solving complex technical problems collaboratively Nice-to-Haves - Experience with large scale model training or distributed inference systems - Familiarity with Ray, Kubeflow, Slurm, or similar distributed scheduling platforms - Experience with InfiniBand, RDMA, or high-performance networking - Experience operating bare metal infrastructure - Familiarity with storage systems commonly used in ML environments - Experience working at an AI infrastructure, cloud, MLOps, or developer tooling company - Contributions to platform engineering, developer infrastructure, or operational tooling projects - Experience writing automation, tooling, or scripts in Python or similar languages Benefits - Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.) - Retirement and financial wellness support (U.S.); Pension contribution (U.K.) - Generous paid time off, plus holidays - Paid parental leave - Professional development support - Wellness and work-from-home stipends - Flexible work environment

• Own the delivery of a scoped set of developer platform capabilities end-to-end (design, implementation, rollout, iteration). • Build and evolve paved roads (golden paths, service templates, scaffolding) that make it easy to deploy, operate, and scale services. • Run tight feedback loops with engineers across product and ML teams; measure adoption and eliminate common friction points. • Drive improvements to GitOps workflows via ArgoCD and Terraform automation via Atlantis. • Harden CI/CD on GitLab CI, including pipeline performance, safety, and developer ergonomics. • Design progressive delivery patterns (canary, blue/green) as reusable platform primitives. • Contribute to SLI/SLO frameworks and shared observability primitives (Prometheus, Grafana, Loki, Tempo, OpenTelemetry). • Participate in the platform team's on-call rotation; reduce toil through automation and better system design. • Improve incident response and postmortem practice so learnings translate into systemic fixes. • Embed secure-by-default patterns into platform templates (secrets, IAM, RBAC, NetworkPolicies). • Partner with security on compliance posture (SOC 2, ISO 27001) without slowing delivery. • Partner with infrastructure/SRE owners on Kubernetes and core cloud foundations (networking, storage, cluster/platform primitives) where it directly improves developer workflows. • Evolve cloud-native abstractions so the platform remains portable and resilient as our footprint grows (GCP today, with future optionality across providers).

Role Description We are seeking a talented and self-motivated Platform/DevOps Engineer to join our growing DevOps team that makes up part of the Platform and Data Engineering function. We engage in designing and managing production and development environments that support the Dotdigital SaaS platform evolution, growing year on year. We collaborate with highly talented cross-functional teams, across Product, Quality Assurance, Software Engineering and Operations functions, to continuously improve business outcomes and achieve corporate goals, through maintaining scalable infrastructure, automation, seamless integration, and innovative solutions. Our product and technical teams are currently based in the UK, Poland, and South Africa and our 180 team members all work from home. We do make office and co-working spaces available, but that choice is up to you. We keep in touch with each other via Slack and Zoom and have a great collaborative culture. To top up our social batteries, we all meet up quarterly in person (we have a meetup per country) and work together for a day, and let off some steam with activities or tech talks. Responsibilities - Design, implement, and maintain scalable infrastructure to support production and development environments. - Automate deployment processes and improve system performance. - Ensure 24/7 platform uptime across the globe. Support operational teams in BAU activities. - Collaborate with cross-functional teams to enhance system reliability and support development and operations initiatives. - Engage in all stages of the DevOps Engineering Life Cycle (concept, define, design, build, test, release, maintain, and retire). - Propose, scope, design, and implement various infrastructure architectures. - Maintain and deploy highly-available, fault-tolerant systems at scale. - Utilize Azure cloud native technologies, Kubernetes, Docker, and configuration management tools. - Work collaboratively with multiple teams to deliver end-to-end products and features. - Keep up to date on modern technologies and trends, advocating for their inclusion within products when appropriate. - Following the successful completion of the probation period, the candidate will be included in the team’s on-call rotation. This involves responding to critical incidents and ensuring platform reliability outside of standard working hours, on a scheduled basis. Qualifications - Strong experience with cloud platforms. We have a strong preference for Azure experience. - Demonstrable scripting experience with PowerShell (Python, Bash is good too). - Strong exposure to cloud native Technologies (Container orchestrators, Immutable infrastructure, Service Mesh). - Experience in Infrastructure as Code, (Terraform, Azure ARM, Bicep) that has to work at scale and in multiple regions. - Comfortable working with versioning tools (Git, Azure Devops, GitHub). - Excellent CI/CD pipeline authoring. Automation is key after all. We use Azure DevOps. - Experience in Observability and Reporting tools and their components (think ElasticSearch, Grafana, Prometheus, Thanos, Raygun). - Know your way around Linux and Windows OS. If you come from a sysadmin background this is cool! Personal - A positive and proactive attitude! We pride ourselves on our company culture, so it’s imperative that you’re a team player and don’t shy away from taking on feedback. We’re here to help each other. - A motivated, coachable, and determined individual. We don’t expect you to know everything, but if you can demonstrate a willingness and desire to learn, we’d love to hear from you. - Impeccable work ethic. Someone who is willing to go the extra mile. - You will be part of a wider Technology Team, so excellent written, verbal and problem-solving skills are a positive. - Excellent interpersonal skills and enjoy networking, public speaking, and cultivating relationships. - Ability to prioritise, and manage time effectively in a parallel project environment. You can evaluate and manage your time and focus without affecting your performance or decision-making. - Detail oriented, highly organized, can work independently and as part of a team. - Display a strong commitment to consistently reach established goals. Benefits - Parental leave - Medical benefits - Paid sick leave - Dotdigital day - Share reward - Wellbeing reward - Wellbeing Days - Loyalty reward - DEI commitment Interview Process - 15min Screening Call with Team Talent. - We’ll send you a small assessment to do offline. We ask you bring your submission so we can chat about it. - You’ll join a video call with two people from our DevOps team and we’ll chat tech, look at your assessment, your previous projects, and do a coding exercise together. This will take around 90 minutes. - We’ll have a final video interview, with our Platform Engineering Director. We’ll talk tech and projects again, but we really encourage questions during this phase. We’re happy to discuss our tech stack, our ambitions, current problems, our processes, or anything else that’s on your mind – nothing’s off limits.

Role Description CALIBRE Systems inc, an employee-owned mission focused solutions and digital transformation company, is looking to hire a Cloud Platform Engineer to deliver Kubernetes-based platform solutions across commercial and government environments. This is a hands-on, customer-facing engineering role operating in a professional services model. You will architect, build, harden, and deploy production-ready Kubernetes platforms using Spectro Cloud across SaaS, on-prem, and fully air-gapped environments. Engagements range from short accelerators to multi-month implementations. Once delivery and knowledge transfer are complete, you move to the next challenge. This is not a long-term operations role. - Openings include: - TS/SCI - TS - Commercial (no clearance required) - What You’ll Do: - Architect and deploy Kubernetes platforms using Spectro Cloud in: - VMware vSphere - Bare metal - AWS, Azure, GCP - Restricted / air-gapped networks - Build and configure clusters from scratch, including control plane, networking, storage, and ingress. - Integrate CI/CD pipelines and container supply chains (build, scan, push, deploy). - Containerize and modernize customer workloads using Helm, OCI registries, and Git-based workflows. - Troubleshoot real-world distributed system issues across: - CNI and DNS - Load balancers and ingress - TLS/certificates - Persistent storage and CSI drivers - Support both connected SaaS-style deployments and fully offline artifact mirroring environments. - Produce clear architecture diagrams, runbooks, and structured knowledge transfer for customer independence. Qualifications - Experience with Kubernetes and cloud platforms. - Proficiency in CI/CD processes and tools. - Strong troubleshooting skills in distributed systems. - Familiarity with containerization technologies. Requirements - Hands-on experience with Spectro Cloud. - Ability to work in a professional services model. - Clear communication skills for customer interactions. Benefits - Employee-owned company structure. - Opportunities for professional growth and development. - Engagement in diverse projects across various environments.