The
Development Head will lead the
software engineering function for our
cloud infrastructure product lines, with a primary emphasis on
AI/GPU and
HPC services. This role encompasses
architecture oversight,
technical strategy, and
team leadership, ensuring that development initiatives align with product and business goals. You’ll partner closely with product management, operations, and customer success teams to deliver cutting-edge, scalable, and secure solutions that cater to demanding enterprise and research workloads.
- Key Responsibilities
- Technical Leadership & Strategy
- Define and drive the technical roadmap for CPU/AI/GPU-enabled cloud infrastructure, ensuring alignment with overall product vision.
- Champion best practices (design patterns, coding standards, CI/CD, DevOps) and foster a culture of innovation and continuous improvement within the development teams.
- Architecture & Design
- Oversee end-to-end system architecture for HPC and CPU/GPU-accelerated software platforms, working with architects and senior engineers.
- Guide decisions around microservices vs. monolithic approaches, API design, database schemas, and infrastructure (e.g., Kubernetes, multi-cloud, edge computing).
- Team Management & Development
- Manage multiple development squads or technical teams, setting objectives, conducting performance reviews, and identifying growth opportunities.
- Recruit, mentor, and retain top engineering talent, promoting a healthy and collaborative work environment that encourages professional growth.
- Collaboration & Cross-Functional Partnership
- Partner with Operations/SRE teams to ensure software reliability, scalability, and efficient GPU resource utilization, building robust release pipelines.
- Quality & Delivery
- Own end-to-end delivery of product releases, ensuring code quality, performance, and adherence to internal and customer-facing SLAs.
- Implement agile methodologies (Scrum, Kanban) or suitable delivery frameworks to balance speed, quality, and predictability.
- Drive the creation and adoption of unit, integration, and performance testing strategies tailored to HPC/AI workloads.
- Innovation & R&D
- Stay abreast of the latest trends in GPU acceleration, HPC frameworks (e.g., CUDA, MPI), AI/ML libraries, and multi-cloud architectures.
- Budget & Resource Planning
- Manage departmental budgets, tool licensing, and hardware procurement (e.g., GPU servers, HPC clusters) in alignment with company goals.
- Ensure cost-effective resource allocation across projects, balancing ROI with innovation needs.
- Security & Compliance
- Ensure development processes meet industry standards (SOC 2, ISO 27001, etc.) and data protection regulations, especially for HPC/AI data sets.
Skills: data protection regulations,architecture,hpc,devops,ai,agile methodologies,cloud infrastructure,architecture oversight,cloud,gpu,software,technical leadership,kubernetes,infrastructure,design,multi-cloud,edge computing