Senior Director, EDA & HPC Engineering Platforms

Technology, Data & Digital · IT Infrastructure & Security · DevOps · Systems Engineering · Data Engineering

In short

As a Senior Director of EDA & HPC Engineering Platforms, you will lead the vision, architecture, and global operations for compute, data, and development infrastructure supporting silicon and systems engineering. This role involves defining a multi-year modernization roadmap across on-premises and hybrid cloud environments, setting technical standards, and building a high-performing organization that partners closely with design and CAD teams. Success hinges on driving engineering productivity, ensuring timely tape-outs, optimizing infrastructure investments, and protecting valuable intellectual property.

Responsibilities

Define and own the multi-year strategy, target-state architecture, and investment roadmap for EDA/HPC platforms.
Lead a global organization of Directors, Managers, Architects, and SREs, fostering a culture of operational excellence and continuous improvement.
Govern architecture through Architecture Decision Records (ADRs), design reviews, and technical standards.
Own the annual operating plan, budget, and capacity investments, presenting business cases to executive leadership.
Define the target state for multi-scheduler operations (IBM LSF, Altair PBS Pro/Accelerator, Slurm) and lead modernization programs.
Deliver job submission APIs, workflow and pipeline orchestration, and self-service capabilities for engineering users.
Own license management strategy across major EDA vendors, integrating license-aware scheduling and policy controls.
Deliver license utilization analytics to inform vendor negotiations.
Own the strategy, architecture, and operations for enterprise SCM and design data management platforms (Git/GitHub, Perforce, DesignSync, ClearCase, SVN).
Define a forward-looking SCM roadmap, including rationalization of legacy platforms.
Establish standards for branching, workspace management, large-file and binary handling, and performance for large design repositories.
Integrate SCM with CI/CD pipelines, regression systems, and artifact repositories.
Own the enterprise Linux/Unix engineering platform, including OS lifecycle, hardening, patching, and EDA tool compatibility certification.
Drive infrastructure-as-code and configuration management at scale using tools like Ansible, Terraform, Puppet/Salt.
Lead container adoption for HPC and engineering workloads (Apptainer/Singularity, Docker, Podman) and orchestration platforms (Kubernetes, OpenShift).
Partner with storage and infrastructure teams on high-performance storage solutions.
Build and lead an analytics and data engineering function to transform platform telemetry into decision systems.
Architect scalable data pipelines and platforms (e.g., Kafka, Spark, Airflow, ClickHouse, Snowflake).
Productize dashboards and self-service analytics covering utilization, job wait times, license efficiency, and engineering productivity.
Deliver capacity planning and forecasting models, including predictive and ML-driven approaches.
Build a converged observability stack for metrics, logs, and traces (Prometheus, Grafana, ELK/OpenSearch, Splunk).
Define SLIs and SLOs for critical engineering services, with high-signal alerting and error budgets.
Implement auto-remediation and self-healing capabilities.
Lead incident management, post-incident reviews, and problem management.
Lead engineering IP classification and least-privilege access models.
Implement secure enclaves and containment for sensitive programs and data.
Build monitoring, audit, and data loss prevention pipelines.
Integrate identity and access management across platforms.
Define the hybrid HPC strategy and reference architectures for cloud burst and cloud-native EDA execution (AWS, Azure, GCP).
Establish patterns for images and tooling, data locality and transfer, and security for cloud HPC.
Lead FinOps practices for cloud spend governance.
Own strategic relationships with EDA vendors, hardware OEMs, and cloud partners.
Lead contract negotiations, renewals, and vendor performance governance.

Requirements

15+ years of progressive experience in HPC, EDA infrastructure, or engineering IT, including 8+ years leading multi-level organizations (managers of managers).
Deep expertise operating mission-critical, large-scale compute grids running multi-vendor EDA flows in semiconductor, systems, or similar engineering environments.
Mastery of scheduler design and operations (IBM LSF required; Altair PBS/Accelerator and Slurm strongly preferred), including queue and fairshare policy, wrappers and pre-execs, and migration/dual-run strategies.
Strong experience with EDA license management (FlexNet/FlexLM, RLM) and license-aware scheduling.
Hands-on leadership of enterprise SCM platforms, including Git/GitHub, Perforce, and DesignSync, with experience in ClearCase or other legacy system migrations.
Strong foundation in Linux/Unix systems engineering at scale, configuration management, and infrastructure-as-code.
Proven experience with containers and orchestration (Apptainer/Singularity, Docker, Kubernetes) in HPC or engineering environments.
Demonstrated leadership of analytics and data engineering initiatives, including data pipelines, analytics databases (e.g., ClickHouse, Snowflake), and BI tools (e.g., Tableau, Power BI).
Proven observability leadership (SLIs/SLOs, alert fidelity, runbooks, self-healing) with hands-on experience in Prometheus/Grafana and/or enterprise APM.
Strong background in engineering IP protection, including classification, RBAC/DRM, secure enclaves, monitoring, and audits, working closely with Security and Legal.
Track record of owning large budgets, building business cases, and leading vendor and contract governance.
Exceptional executive communication skills, with the ability to translate complex technical topics into business outcomes.

Desired Qualifications

Experience leading hybrid or cloud HPC for EDA workloads on AWS, Azure, or GCP, including FinOps practices.
Experience with high-performance storage platforms (NetApp, Weka, GPFS/Storage Scale, Lustre, VAST).
Familiarity with CI/CD and DevOps tooling (Jenkins, GitHub Actions, GitLab CI, Artifactory).
Experience applying AI/ML to scheduling, capacity forecasting, or operational analytics.
Experience supporting export-controlled or regulated engineering programs.
Scripting and automation proficiency (Python, Bash, Perl, Tcl).
Bachelor's degree in Computer Science, Computer/Electrical Engineering, or a related field; Master's degree preferred.

Benefits

Competitive annual discretionary bonus program.
Opportunity for annual RSU grants.
Highly competitive benefits package designed to support your success at work, at home, and at play.

Skills

HPCEDALinuxUnixGitGitHubPerforceDesignSyncClearCaseAnsibleTerraformPuppetSaltApptainerSingularityDockerPodmanKubernetesOpenShiftKafkaSparkAirflowClickHouseSnowflakeDatabricksTableauPower BIGrafanaPrometheusSplunkIBM LSFAltair PBSSlurmFlexLMRLMNetAppWekaIBM Storage ScaleGPFSLustreVASTPythonBashPerlTcl

#IT Management#HPC#EDA#Engineering Platforms#Silicon Engineering#Systems Engineering#Compute Infrastructure#Data Infrastructure#Development Infrastructure#HPC Grids#Intelligent Scheduling#EDA License Orchestration#Source Code Management#Design Data Management#Linux#Unix#Container Platforms#Observability#Analytics#Data Engineering#Engineering IP Protection#On-premises Data Centers#Hybrid Cloud#Technical Standards#Engineering Productivity#Tape-out Schedules#Infrastructure Investment#Intellectual Property Security#SRE#CI/CD#DevOps#FinOps#AI/ML#Scripting#Automation