DNEG
Infrastructure / DevOps Lead
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Brahma AI operates at the intersection of enterprise Media Asset Management (MAM) and cutting-edge generative media. We build and scale industry-leading generative AI models, including hyper-realistic digital humans (ATMAN) and multilingual voice synthesis (VAANI), for world-class enterprise clients in entertainment, sports, healthcare, and retail.
Role Overview
We are looking for a Lead Infrastructure / DevOps Engineer to lead our core AI Platform & Infrastructure team. Reporting directly to the VP of Engineering, you will guide a team of 7 engineers responsible for powering our high-performance GPU infrastructure, multi-cloud setup (with GCP as our primary provider), ML model training pipelines, and containerised orchestration environments.
This role balances technical leadership, team management, cloud resource optimisation, and high-level architectural oversight. You will ensure our research and engineering teams have the fast, scalable, and reliable compute environments necessary to train and deploy state-of-the-art AI models.
Key Responsibilities
People, Team & Process Leadership (50%)
- Team Management: Lead, mentor, and grow a team of 7 DevOps and Infrastructure engineers through regular 1:1s, performance reviews, and career pathing.
- Sprint & Operational Delivery: Drive agile delivery, sprint planning, and backlog prioritisation to align infrastructure deliverables with AI research and product roadmaps.
- Engineering Standards: Establish best practices for Reliability Engineering, Infrastructure-as-Code (IaC), continuous integration, and incident post-mortems.
- Cross-Functional Alignment: Act as the primary technical bridge between infrastructure, ML researchers, AI application developers, and the VP of Engineering.
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Resource Management & FinOps (25%)
- GPU & Multi-Cloud Management: Manage high-density GPU clusters across a multi-cloud ecosystem (primarily GCP) optimised for large custom AI model training and real-time inference workflows.
- FinOps & Cost Control: Oversee infrastructure consumption, track cloud/hardware costs, negotiate vendor terms, and optimise GPU utilisation to maintain cost efficiency.
- High-Performance Storage: Oversee high-throughput storage and caching solutions engineered for ultra-fast data retrieval and low-latency access.
Architecture, Engineering & Compliance (25%)
- Technical Escalation & Hands-On Oversight: Serve as the senior technical escalation point for complex infrastructure incidents and architecture decisions.
- Automation & IaC: Standardise platform deployments using Infrastructure as Code (e.g., Terraform/OpenTofu) and modern container orchestration (Kubernetes).
- Security & Compliance Collaboration: Partner with security stakeholders to ensure our AI training environments meet industry security standards (e.g., MPA Best Practices, ISO 27001, SOC 2).
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Must Haves
- Leadership Experience: Proven track record leading or managing a team of 5+ infrastructure, platform, or DevOps engineers.
- AI/GPU Infrastructure: Hands-on experience architecting and managing GPU-intensive workloads (NVIDIA clusters, cloud AI accelerators) for compute-heavy applications.
- Multi-Cloud & Orchestration: Expertise with Kubernetes, Docker, Terraform (or OpenTofu), and multi-cloud environments (with strong hands-on GCP experience).
- High-Performance Storage: Demonstrated experience designing, optimising, and maintaining high-performance storage architectures and caching layers for demanding compute workloads.
- Cloud & Resource Management: Strong experience with cloud cost governance (FinOps), capacity planning, and vendor interaction.
- Communication: Exceptional stakeholder management skills with the ability to bridge business requirements and deep technical infrastructure details.
Nice to Have
- Experience managing physical data centres, co-location facilities, or hybrid infrastructure environments.
- Working knowledge of ML orchestration frameworks (e.g., Ray, Slurm, Kubeflow).
- Background in media pipelines, VFX tooling, or media compliance standards (MPA, ISO 27001).
- Prior experience working in a hybrid startup/scale-up environment.
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