Our client is looking for an engineer with high-performance computing (HPC) and site-reliability experience to keep their growing multi-cloud AI infrastructure reliable and efficient. You will investigate hard operational problems across compute, accelerators, workload scheduling, storage, and networking, and turn what you learn into proactive detection, diagnosis, and safe automated remediation, including AI-powered agents.

Success here starts with understanding how HPC infrastructure behaves in production and learning unfamiliar systems rapid. Prior experience building or orchestrating AI agents is welcome but not required.

Req# (phone hidden)

The recruiting efforts for this position are intended to fill an existing vacancy for a new position.

Responsibilities

- Build a working understanding of multi-cloud HPC architecture (clusters, schedulers, accelerators, storage, networking, authentication) and keep it current as the infrastructure changes
- Find reliability and performance problems proactively, correlating logs, metrics, and events across cloud providers to build a clear incident picture and spot gaps in telemetry
- Diagnose complex issues end to end across Linux hosts, containers, schedulers, distributed workloads, storage, networking, and accelerators, isolating root cause rather than treating symptoms
- Turn proven investigations into repeatable tooling and agent-enabled workflows for detection, diagnosis, and bounded remediation, with safety built in: scoped permissions, precondition checks, human approval where needed, rollback, and post-change verification
- Strengthen observability and monitoring, measure whether the automation actually works (accuracy, recovery time, recurrence, false positives), and partner with infrastructure, research, security, and cloud-provider teams to turn incident lessons into durable fixes

Requirements

- Operations experience with production HPC, GPU/accelerator clusters, or large-scale distributed compute in a reliability-focused engineering role
- Strong Linux and networking skills, debugging failures across processes, containers, storage I/O, DNS, connectivity, and authentication
- Correlates telemetry across multiple cloud environments using tools such as Prometheus, Grafana, OpenTelemetry, or centralized logging, rather than relying on a single dashboard
- Writes and maintains automation in a language such as Python or Go,



and has owned complex production investigations from symptom through root cause to a verified, lasting fix

Nice to have

- Hands-on with HPC scheduling or cluster orchestration (Slurm, Kubernetes, or similar), and an understanding of how infrastructure health affects workload placement and completion
- Supporting AI training or accelerator-intensive workloads: GPU/TPU health, distributed-job failures, interconnect problems, data-loading bottlenecks, or checkpointing
- Experience across clouds such as AWS, GCP, CoreWeave, or OCI and their native observability services. You do not need every provider named here
- HPC storage and networking (NFS/POSIX, Lustre, object storage, RDMA/InfiniBand or RoCE), infrastructure-as-code and deployment tooling (Terraform, Helm, cluster operators), and failure-injection or replayable incident testing
- Building, integrating, evaluating, or orchestrating AI agents for infrastructure operations (tool interfaces, permissions, verifying agent actions)
- Welcome, but not required; strong HPC operations and SRE skills are the foundation of this role

We offer

- Extended Healthcare with Prescription Drugs, Dental and Vision, and Healthcare Spending Account (Company Paid)
- Life and AD&D; Insurance (Company Paid)
- Employee Assistance Program (Company Paid)
- Telehealth (Company Paid)
- Short-term Disability (Company Paid)
- Long-Term Disability
- Paid Time Off (including vacation and sick days)
- Registered Retirement Savings Plan (RRSP) with Company match
- Maternity/Parental/Adoption Leave Top-up
- Employee Stock Purchase Program
- Critical Illness Insurance
- Employee Discounts
- Unlimited access to LinkedIn learning solutions

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our clients, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions,



and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Engineer the Future with a Career at EPAM

This posting includes a salary range EPAM Canada would reasonably expect to pay the selected candidate. Individual compensation offers within the range are based on a variety of factors, including, but not limited to, experience, credentials, education, training, the demand for the role, skillset, and overall business and local labour market considerations. Most candidates are hired at a salary within the range disclosed. Salary range: CA$155,000-CA$175,000. In addition, the details highlighted in this job posting above are a general description of all other expected benefits and compensation for the position.

EPAM Canada welcomes and encourages applications from candidates with disabilities. Please contact WFA Human Resource CA [email protected] if you have questions in this regard, or if you require an accommodation to complete the application process. Click here to review EPAM’s Accessibility for Ontarians with Disabilities Accessibility Policies and Multi-Year Access.

An artificial intelligence system is software that is developed with one or more techniques that can, for a given set of human-defined objectives, using algorithmic information processing, generate outputs such as content, predictions, recommendations, or decisions with varying levels of autonomy (“AI”). Tasks that humans have traditionally done by thinking and reasoning are increasingly being done by, or with the help of, AI to help create efficiencies.EPAM may use AI during the recruitment process, in connection with collecting or processing your personal data. Some (non-exhaustive) examples of tasks that EPAM may use AI for include conducting initial screening, creating transcripts of interviews, and assessing applications/CVs against defined job description criteria to make suggestions to the individuals evaluating your candidacy.Your personal data and the results of any processing are not shared with AI applications outside of EPAM infrastructure. While EPAM may use AI to help create efficiencies during the recruitment process, EPAM does not use AI to make hiring decisions, which is done by EPAM Talent Acquisition and management.

📌 Lead HPC Systems Engineer (Canada)
🏢 EPAM Systems
📍 Canada