• Document existing business operations, workflows, and technical practices across applications and infrastructure. • Analyze current processes against recognized industry and IT best practices, identifying opportunities for improvement. • Develop Plans of Action and Milestones (POA&Ms) to guide the evolution of systems, processes, and operational maturity. • Serve as a senior member of a cross‑functional team, providing expert insight into the business implications of applying new or enhanced systems. • Support the full lifecycle of IT initiatives, from requirements and design through implementation and sustainment. • Collaborate with stakeholders to ensure system solutions align with organizational goals, compliance requirements, and operational needs.

Role Description We’re hiring a Staff HPC Systems Software Engineer to define the technical direction and evolution of a core HPC platform domain at Nscale. In this role, you will operate beyond a single team, shaping how multiple teams build, automate, and run Slurm-based capabilities within Nscale’s wider cloud-native platform. You’ll work across engineering boundaries to bring coherence to architecture, interfaces, lifecycle models, and operational approaches, while partnering closely with teams working on platform tooling, infrastructure APIs, identity systems, and Kubernetes-adjacent systems. This is a high-impact staff-level role for someone who combines deep hands-on software engineering with strong systems judgement. Your work will help ensure Nscale’s HPC services are robust, supportable, and maintainable, while creating leverage through shared patterns, reusable implementations, and clear technical direction across ambiguous, business-critical problem spaces. What you'll be doing - Domain Architecture & Technical Direction - Own and evolve the technical direction for a defined HPC systems domain, such as Slurm platform architecture, scheduler integrations, cluster lifecycle, workload environments, or service automation. - Make architectural decisions that balance software quality, operational realities, customer needs, and long-term maintainability. - Define how proven Slurm implementations should be packaged, automated, and exposed as a service. - Resolve ambiguity around ownership, interfaces, lifecycle boundaries, and operating models across teams. - Act as the technical escalation point for the most complex issues within the domain. - Cross-Team Engineering Leverage - Establish shared patterns and standards for automation, service lifecycle management, observability, reliability, and supportability across the HPC platform. - Drive cross-team design for integrations between Slurm, Kubernetes-adjacent systems, infrastructure APIs, identity systems, and platform tooling. - Create reusable modules, automation, deployment patterns, and reference implementations that increase engineering leverage. - Identify and correct avoidable technical divergence, duplicated effort, and fragile operating models. - Ensure domain designs reflect the realities of GPU scheduling, HPC networking, performance isolation, and production operations. - Delivery, Reliability & Influence - Lead technically critical initiatives spanning 2–4 teams or a defined HPC platform area. - Unblock delivery by clarifying technical direction and reducing ambiguity in complex system design problems. - Contribute hands-on where needed to de-risk or accelerate critical work. - Influence engineering teams without formal authority through strong judgement, design clarity, and practical solutions. - Partner with adjacent cloud-native software engineers so HPC implementations build on shared platform patterns rather than separate ones. KPIs - Technical direction across a defined HPC domain - Delivery of critical initiatives across 2–4 teams - Reduction in technical divergence and duplicated effort - Reliability and supportability of Slurm-based HPC services Qualifications - Extensive experience designing and building production software and automation for HPC systems, especially Slurm-based environments. - Strong track record of writing maintainable, testable, and resilient software in Go, Python, or similar languages. - Proven ability to define technical direction across a domain spanning multiple teams or services. - Strong understanding of Slurm internals, scheduler behaviour, cluster lifecycle concerns, and operational trade-offs. - Strong practical understanding of GPU-backed infrastructure and HPC networking, including InfiniBand, RoCE, RDMA, and performance-sensitive workload characteristics. - Experience integrating HPC systems with cloud-native platforms, APIs, or service delivery models. - Experience creating engineering leverage through standards, reusable patterns, shared tooling, and architectural clarity. - Strong judgement in balancing short-term delivery with long-term platform health and supportability. - Strong written and verbal communication skills, with the ability to align multiple teams around a coherent technical direction. - Experience with other schedulers or batch systems such as Kueue is valuable. Benefits - Highly competitive US compensation package (base + bonus + equity), with performance reviews every 12 months. - Join one of the fastest-growing AI infrastructure companies — your chance to directly shape how global AI capacity is planned and deployed. - Expect a dynamic progression plan tailored to your ambitions. Grow by leading critical cross-functional initiatives and shaping capital strategy — always with our full support. - Human-First Flexibility: We treat you as humans first. Our flexible workplace trusts Nscalers to deliver, giving you the autonomy to shape your day around life's moments.

• Define and own roadmap and execution plans for ecosystem integrations, deployment connectors, policy content, compliance, security, and risk evaluation capabilities • Translate Liquibase’s strategic direction into clear product outcomes, phased initiatives, measurable business impact, and differentiated market positioning • Help establish Liquibase as the enterprise leader in Database Change Governance by clearly articulating customer pain, market opportunity, competitive differentiation, and business value • Engage deeply with enterprise customers, prospects, field teams, partners, and internal stakeholders to understand pain points across DevOps, data platforms, security, compliance, audit, and enterprise change management • Turn strategy into clear requirements, epics, user stories, acceptance criteria, release plans, and measurable success criteria • Partner closely with engineering, architecture, design, documentation, security, customer success, sales, marketing, and leadership to deliver high-quality product capabilities to market • Use customer evidence, product telemetry, market analysis, competitive insight, adoption data, and business impact to prioritize product investments • Define and monitor KPIs that measure product success, including governance adoption, policy coverage, integration adoption, compliance workflow efficiency, enterprise expansion impact, and time-to-value for new enterprise customers • Support positioning, messaging, enablement, customer validation, and go-to-market execution in partnership with product marketing, sales, customer success, and leadership

• Work side-by-side with the concept architect to convert advanced system ideas into technical specifications, service maps, data models, APIs, schemas, tests, and deployment plans. • Translate verbal and written design guidance into architecture diagrams, implementation backlogs, acceptance criteria, and working prototypes. • Identify ambiguity, missing assumptions, engineering risks, security issues, and implementation conflicts. • Help turn an evolving concept architecture into reproducible, testable, maintainable software. • Build production-grade Python services, APIs, data pipelines, background workers, and orchestration logic. • Design clean service boundaries for ingestion, entity resolution, evidence management, review workflows, reporting, audit logging, and model integration. • Design and implement relational schemas, graph models, object-storage structures, retrieval indexes, and audit records. • Build canonical identity and entity-linking systems that reconcile conflicting real-world records. • Support relationship topology, ownership mapping, provider-network analysis, and source-conflict preservation. • Integrate model-serving infrastructure such as vLLM, KServe, Ray Serve, and Hugging Face, or equivalent tools where appropriate. • Deploy services using Docker, Kubernetes, Helm, GitOps, CI/CD, RBAC, secrets management, observability, and secure environment practices.