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Senior Engineer, Compute at AHEAD, Gurugram

Senior Engineer, Compute at AHEAD in Gurugram. Apply with swipeandhired.

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.

At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.

We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.

We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.

The High-Performance Computing Compute Engineer is primarily responsible for the overall health and maintenance of the physical cluster and server technologies in our managed services customer's environments. Our Compute Engineers are a valued member of the Managed Services Infrastructure Practice responsible for Tier 3 incident management, service request management and change management infrastructure support for all Managed Services customers.

Key Responsibilities
Provide enterprise-level operational support to Managed Services customers for incident, problem, and change management activities

Manage and maintain large-scale HPC and GPU compute clusters for AI training, inference, simulation, and data-intensive workloads

Deploy and administer Linux-based compute environments, including operating systems, drivers, firmware, CUDA or equivalent accelerator software, libraries, and runtime dependencies

Operate workload scheduling and orchestration platforms such as Slurm, Kubernetes, Ray, or comparable technologies

Benchmark and tune end-to-end workload performance

Troubleshoot complex failures from bare metal and firmware through the operating system, drivers, middleware, distributed frameworks, and user applications in step with other teams

Build automation for provisioning, configuration management, patching, validation, monitoring, and lifecycle management using Python, Bash, Ansible, Terraform, or similar tools

Develop operational dashboards, alerts, health checks, and capacity-planning processes that improve availability and resource utilization

Establish repeatable processes for incident response, root-cause analysis, change management, and operational readiness

Create technical documentation, runbooks, architecture diagrams, and user guidance for HPC and AI platforms

Participate in on-call rotation

Completion of training and certification as assigned to further skills and knowledge

Required Qualifications

Bachelor’s degree in computer science, computer engineering, electrical engineering, or a related technical field; equivalent practical experience may be considered

Four or more years of experience deploying, operating, or engineering HPC, GPU, distributed systems, or cloud infrastructure

Strong Linux or UNIX systems administration experience in production environments

Hands-on experience with GPU computing, accelerator infrastructure, or large-scale AI workloads

Experience with at least one workload manager or orchestrator, such as Slurm, Kubernetes, Run:ai, or PBS

Strong scripting and automation skills in Python, Bash, or a comparable language

Working knowledge of networking fundamentals, including TCP/IP, DNS, DHCP, routing, firewalls, Ethernet, and high-speed interconnects

Experience diagnosing performance, reliability, and capacity issues across multiple infrastructure layers in a physical datacenter environment

Ability to document systems clearly and communicate effectively with both technical and nontechnical stakeholders

Demonstrated ability to work independently, prioritize operational risk, and collaborate in a fast-moving environment

Preferred Qualifications
Experience with NVIDIA GPU platforms, CUDA, NCCL, DGX, HGX, or comparable accelerator technologies

Experience with InfiniBand, RoCE, RDMA, congestion control, or lossless network fabrics

Experience with Slurm configuration, fair-share scheduling, QoS, accounting, job arrays, and high-throughput workload management

Experience with Kubernetes, GPU operators, container runtimes, Helm, or cloud-native infrastructure

Experience with parallel and distributed storage platforms such as Lustre, GPFS, BeeGFS, Ceph, ZFS, or XFS

Familiarity with PyTorch, TensorFlow, MPI, OpenMP, UCX, NCCL, Ray, or distributed model-training frameworks

Experience with observability platforms, telemetry pipelines, and performance-profiling tools

Experience with configuration management, infrastructure as code, CI/CD, GitOps, or immutable infrastructure practices

Experience supporting LLM training, fine-tuning, retrieval-augmented generation, model serving, or inference platforms

Why AHEAD:

Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.

We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.

India Employment Benefits include:
Comprehensive health insurance coverage for employees, with options to extend coverage to dependents
Paid time off and company holidays, along with additional leave benefits as per policy
Flexible work arrangements, supporting work-life balance
Learning and development opportunities to support continuous growth and upskilling
Employee wellness initiatives and programs focused on physical and mental well-being
Retirement and statutory benefits in line with India regulations
Inclusive and people-first culture, with a strong focus on collaboration and ownership