Principal Engineer

Job description

Job Title: Principal Forward Deployed Engineer, AI Factory (Infrastructure) - NVIDIA Ecosystem Business Unit Team: Leads the infrastructure workstream of an AI Factory FDE pod; works with the Platform and AI Software Principal and the pod's FDE III engineers Travel: travel as required to client sites and data centers; indicative 40-60% Role Summary HCLTech is seeking a Principal Forward Deployed Engineer to own the physical and fabric layer of client AI Factories on NVIDIA platforms. The Principal takes the solution architect's reference design to detailed design, owns site readiness and acceptance with the OEM and NVIDIA, and leads bring-up and validation of GPU clusters across the pod's engagements, handing over a scheduler-ready factory. The role also coaches FDE III and FDE II engineers and sets infrastructure standards for the bench. Key Responsibilities Key Responsibilities AI Factory Build & Deployment Deploy the AI Factory infrastructure stack (Hopper and Blackwell class compute, NVLink and NVSwitch, InfiniBand / Spectrum-X fabrics, BlueField DPUs, storage for AI) to the architect-approved NVIDIA reference design Lead bare-metal bring-up and system software: firmware, drivers, OS images, BCM / Mission Control , NVLink partitioning Configure and tune InfiniBand / RoCE fabrics and high-performance storage to the approved design Run cluster validation ( NCCL , HPL, burn-in), telemetry and XID troubleshooting; isolate faults across network, firmware and scheduler layers Site Readiness & Acceptance Check power, cooling and rack-layout readiness against the sizing; flag gaps found on site Run acceptance testing with the OEM and NVIDIA and produce validation evidence Produce as-built documentation and operable runbooks Automation Build and maintain bring-up automation (Ansible, Python, Bash) and firmware lifecycle tooling for repeatable builds Client & Team Collaboration Hand over a scheduler-ready cluster to the pod's platform FDEs with agreed interfaces Brief client technical teams; contribute technical inputs to presales scoping and estimates Convert each engagement into reusable bring-up checklists and blueprints Technical Leadership & Ownership (Principal) Own detailed design (L1 to L0) from the solution architect's reference architecture, sized for workload, power and cooling Own site readiness and acceptance with the OEM and NVIDIA; sign off cluster readiness Lead the infrastructure workstream across the pod's engagements; resolve the hardest cross-layer faults with NVIDIA and OEM engineering Coach and review FDE III and FDE II engineers; set bring-up and validation standards Engage client infrastructure leadership and NVIDIA counterparts Skill Requirements Domain Target level What this domain covers AI infrastructure & systems 4 - Expert Physical and fabric layer of the AI Factory: GPU servers and rack-scale systems , InfiniBand / RoCE networking, high-performance storage , firmware and bare-metal bring-up , cluster validation and fault isolation . Platform, orchestration & inference 3 - Proficient Software layer that makes the cluster usable: Kubernetes and SLURM scheduling, GPU sharing and quotas , multi-tenancy , cluster management ( BCM , Run:ai ), and model serving (NIM, vLLM, Triton, TensorRT-LLM) tuned for latency, throughput and cost per token . DevOps & control-plane scripting 3 - Proficient Automation of the factory lifecycle: infrastructure-as-code , GitOps, CI/CD, provisioning and tenant-onboarding scripts, operators and APIs, observability as code . Data & applied AI 2 - Working Data pipelines and use-case delivery on the factory: fine-tuning, RAG and agentic workflows , evaluation and guardrails. Security, governance & sovereignty 3 - Proficient Securing and governing the factory: RBAC and tenant isolation , secrets management , hardening, audit, confidential computing , data residency , sovereign and air-gapped builds . Presales & client engagement 3 - Proficient Presales and client-embedded delivery: technical scoping inputs, client technical sessions , TCO inputs, as-built documentation , and handover to Delivery Teams. Other Requirements Required Skills & Experience 12+ years of experience, including 5+ years deploying or operating GPU / HPC infrastructure Hands-on InfiniBand or RoCEv2 / RDMA configuration and tuning Bare-metal provisioning experience (MAAS, BCM , Redfish / BMC) and Linux at depth Automation skills (Ansible, Python, Bash) for repeatable bring-up Comfortable debugging across network, firmware and scheduler layers under client pressure Client-facing experience ; comfortable working on-site in client data centers Record of designing and leading GPU cluster builds, including OEM acceptance , and of leading engineers on multi-month deployments Preferred NVIDIA-Certified Associate / Professional credentials (AI infrastructure and operations) Experience with rack-scale systems (GB200 / GB300 NVL72 ) and Mission Control Parallel file systems or AI-tier storage (Ceph, WEKA, VAST, DDN) Power and liquid-cooling fundamentals for GPU data centers SLURM or Run:ai administration; CKA Key Performance Indicators Cluster builds delivered on schedule and passing validation ( NCCL , burn-in) at first attempt Time from hardware arrival to first production workload Acceptance sign-off with the OEM and NVIDIA without rework Defects and escalations after handover Reusable bring-up assets contributed per engagement NVIDIA certifications completed against the agreed path Maximum Salary (US): 220000 Minimum Salary (US): 200000 Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. Compensation and Benefits A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program; 401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per year. Disclaimer Privacy Statement Terms of use Sitemap Raise a Grievance We use cookies on our site. Please read more about cookies policy here. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Copyright © 2026 HCL Technologies Limited Cookie Consent Manager When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. 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