Lightning AI

• Drive execution across multiple infrastructure programs, including network builds and upgrades, storage initiatives, datacenter builds and expansions, and hardware/platform rollouts • Own program planning, milestone definition, and dependency management across parallel workstreams • Partner with Infra Engineering, Network, DC Operations, Hardware, Security, and Platform teams to align scope, timelines, and delivery • Coordinate execution across initiatives such as: • Network expansions, upgrades, and large-scale migrations • Datacenter expansions and capacity growth • Hardware bring-up and infrastructure readiness • Next-generation platform rollouts (e.g. new GPU architectures), ensuring end-to-end readiness across infrastructure layers • Drive cross-functional alignment to ensure infrastructure is ready for deployment, bring-up, and customer usage • Manage risks, blockers, and dependencies across engineering and operations teams • Provide clear, concise program updates to leadership, highlighting progress, risks, and mitigation plans • Operate effectively in a fast-moving, ambiguous environment with shifting priorities • Contribute to improving execution frameworks, tooling, and program visibility across the infrastructure organization

Title: Infrastructure Engineer Observability Location: United States Job Description: New York, New York, United States; Remote; San Francisco, California, United States; Seattle, Washington, United States Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. What We’re Looking For Lightning AI is seeking an Observability Infrastructure Engineer to join our Infrastructure Engineering team. In this role, you will own and evolve observability systems across large-scale, GPU-enabled bare-metal infrastructure. You’ll operate at the intersection of infrastructure, data, and product, building platforms for metrics, logs, traces, and alerting that power both internal operations and customer-facing visibility. You will play a key role in productizing observability, enabling scalable, multi-tenant monitoring experiences while keeping pace with rapid infrastructure buildouts. This includes designing telemetry pipelines, improving signal quality, and delivering actionable insights that ensure reliability and transparency across our platform. We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time. What You’ll Do Observability Platform & Productization - Own and evolve a scalable observability platform spanning metrics, logs, traces, and events - Drive the productization of observability capabilities for both internal teams and external customers - Design multi-tenant observability systems with scoped access, RBAC, and customer-facing visibility - Continuously improve observability systems to keep pace with rapid infrastructure buildouts Telemetry & Data Pipelines - Design and operate telemetry pipelines ingesting data from GPUs, CPUs, networking (Ethernet & InfiniBand), containers, APIs, and BMC/Redfish - Build systems to correlate signals across infrastructure layers to enable faster debugging and root cause analysis - Implement streaming and real-time data pipelines using tools such as Kafka, OTEL, Promtail, or similar Alerting, Reliability & Insights - Design and implement noise-resistant alerting systems to improve signal quality and reduce operational load - Create dashboards and alerting for InfraOps, Engineering, and Customer Success teams - Build automated insights and enable proactive detection, forecasting, and system health visibility at scale Systems & Infrastructure Engineering - Contribute to broader infrastructure engineering projects beyond observability - Partner with infrastructure and platform teams to embed observability into core systems and workflows - Support large-scale, distributed systems across compute, networking, and storage environments Cross-Functional Collaboration - Work closely with customer-facing teams to deliver external observability experiences - Collaborate with engineering, operations, and support teams to improve system transparency and reliability - Help define best practices for observability across the organization What You’ll Need Required Qualifications - 5+ years of experience in infrastructure engineering, SRE, or observability-focused roles - Strong experience with monitoring systems such as Prometheus, Grafana, ELK, or VictoriaMetrics - Experience building and operating observability platforms at scale - Proficiency in Python, Go, or bash for automation and data integration - Familiarity with containerized environments and Kubernetes observability - Experience with streaming telemetry pipelines (Kafka, OTEL, Promtail, or equivalent) - Experience with multi-tenant monitoring architectures - Strong written and verbal communication skills Ideal Experience - Experience with GPU observability, particularly NVIDIA DCGM - Experience monitoring large-scale GPU or HPC clusters - Familiarity with InfiniBand fabric observability - Experience building customer-facing or productized infrastructure systems - Experience with correlation engines, RCA workflows, or predictive alerting systems - Broad exposure to infrastructure domains including networking, storage, and provisioning Compensation We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $180,000 - $200,000 USD Benefits and Perks We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role. Benefits include: - 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 At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

• Design and deploy scalable spine/leaf network architectures for AI data centers • Engineer high-performance Ethernet fabrics supporting GPU clusters and AI workloads • Build and maintain EVPN/VXLAN, BGP, and high-speed routing environments • Optimize east-west traffic flows for AI training and inference operations • Support RoCE/RDMA networking and low-latency transport technologies • Support backbone, DCI, WAN, and edge connectivity solutions. • Collaborate with compute, storage, AI platform, and operations teams to deliver integrated infrastructure solutions • Develop automation and Infrastructure-as-Code (IaC) solutions for network provisioning and operations • Troubleshoot complex network, performance, and congestion issues across distributed environments • Improve network observability, telemetry, and operational visibility

Role Description We’re in search of a well-rounded Senior Technical Recruiter to play a critical role in building Voltage Park’s BFT (best functioning team). We’re looking for somebody with start-up or MANGO-level tech experience who understands how the different roles within a tech company fit together – ideally, you’ve worked across multiple teams, such as engineering, product and sales. You’ll be championing inclusive, equitable hiring processes and providing a best-in-class candidate experience, while building trust with teams throughout our organization – starting with our AI software engineering group and expanding to other teams within the org. What You'll Do - Full cycle recruiting for tech roles across the organization, with a focus on our AI software engineering, infrastructure, and product teams - Sourcing, screening, and interviewing candidates - Managing negotiations and offers - Building a diverse pipeline of candidates, including those who are traditionally excluded from the tech space - Helping to maintain and improve an equitable and scalable interview process - Provide an exceptional experience for all candidates, whether they get to offer or not, with an emphasis on communication and responsiveness - Be an active participant in online and in-person communities, helping to build our brand and your network Qualifications - 7+ years of experience as a technical recruiter hiring software engineers, including experience in a high-growth tech company - An enthusiasm for AI – you’re a regular user of new AI technology in work and in life - A deep commitment to building an inclusive, equitable hiring culture - Proactive communication – whether it’s to candidates, or your own hiring managers and team, you keep folks in the know - Bias to action - you’re comfortable with being pleasantly persistent to help move jobs and offers forward - You’re a networker, and well connected within the Seattle tech community - A respect for scalable processes, and a natural inclination to build and improve on those in place - ATS expertise (we use Greenhouse, but Lever, or similar experience also counts) - Phenomenal customer service skills, with a compassion for candidates in the job-seeking process - Ability to remain calm under pressure and adapt to changing priorities - High emotional intelligence and excellent communication skills with a track record of developing and maintaining cooperative working relationships with and among a diverse group of stakeholders at all levels 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

• At the direction of the Manager of Infrastructure Operations, design, build, and roll out new platforms and patterns to minimize incidents and enable customer facing and internal features. • Deploy updates and improvements to support both Voltage Park’s internal and end customer use cases. • Collaborate with colleagues in Infrastructure Engineering, Network Operations, Customer Success and Software and Platform Development Teams. • Participate in the on-call rotation which is evenly distributed across all team members in a primary / secondary pattern where you are primary then move to a secondary position.

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