Sr. Manager, AI Platform Engineering

Description and Requirements

LATC is seeking an accomplished Senior Infrastructure & Platform Engineer to take a leadership role within our AI Technology Center. In this senior position, you will architect, build, and evolve the large-scale infrastructure and platforms that underpin software and AI model development, deployment, and operation across the organization. You will serve as a technical authority on infrastructure strategy, mentor junior engineers, drive best practices, and collaborate cross-functionally with research, engineering, and product teams. Your deep expertise will be instrumental in scaling our AI capabilities and ensuring production-grade reliability, performance, and security. If you are passionate about making Smarter Technology for All, come help us realize our Hybrid AI vision! #LATC

Responsibilities

• Infrastructure & Platform Strategy and Architecture: Define and drive the long-term infrastructure strategy. Architect scalable, cost-efficient, and resilient compute, storage, and networking solutions that support the full AI lifecycle from experimentation through production.
• Technical Leadership and Mentorship: Serve as a technical lead, line manager and mentor to your team of platform and infrastructure engineers, establishing engineering standards, conducting design reviews, and fostering a culture of operational excellence across the team.
• Advanced Automation and CI/CD: Architect and maintain sophisticated automation pipelines for Software development and AI model training, evaluation, testing, and deployment. Champion infrastructure-as-code practices and drive continuous improvement of CI/CD workflows.
• Cross-Functional Collaboration: Partner with data scientists, ML engineers, product managers, and leadership to align infrastructure capabilities with research and business objectives. Act as the primary infrastructure point of contact for cross-team initiatives.
• Performance Engineering: Lead efforts to profile, benchmark, and optimize AI infrastructure and model serving for throughput, latency, GPU utilization, scalability, and cost efficiency at scale.
• Security, Compliance, and Governance: Establish and enforce security best practices, access controls, and compliance frameworks across AI infrastructure. Ensure adherence to relevant regulatory requirements and internal governance policies.
• Capacity Planning and Cost Management: Own capacity forecasting, resource planning, and cost optimization for GPU clusters and associated infrastructure, balancing performance needs with budget constraints.

Qualifications

• Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Advanced degree preferred.
• 12+ years of experience in software engineering, infrastructure engineering, DevOps/SRE, or a related field, with at least 4 years focused on AI/ML infrastructure.
• Demonstrated experience leading or mentoring engineering teams on infrastructure projects.
• Deep expertise in computer systems, distributed systems, and cloud computing architectures.
• Experience leading 24/7 managed services and operations teams.
• Expert-level Linux system administration, including package management, user/group management, file system internals, shell scripting Bash), networking, and system configuration systemd, kernel tuning).
• Strong proficiency in Python and at least one additional systems language Go, C++, Rust, Java).
• Deep experience with AI-specific hardware and software stacks NVIDIA GPUs, CUDA, cuDNN, NCCL, InfiniBand/RoCE networking).
• Proven track record managing high-performance computing (HPC) environments, including job scheduling, resource allocation, cluster maintenance, and performance tuning.
• Strong architectural thinking with the ability to balance trade-offs across performance, reliability, security, and cost.
• Excellent communication and collaboration skills, with the ability to influence technical decisions across teams and present to senior leadership.
• Ability to thrive in a fast-paced, ambiguous environment and drive clarity through technical leadership.
• Hands-on experience with major cloud platforms AWS, GCP, Azure) and hybrid cloud architectures.
• Advanced experience with containerization (Docker) and orchestration (Kubernetes), including custom operators, Helm charts, and GPU scheduling plugins.
• Expertise with observability stacks Prometheus, Grafana, ELK/OpenSearch, Datadog) for infrastructure and model monitoring.
• Experience with infrastructure-as-code tools Terraform, Ansible, Pulumi).

Bonus Points

• Experience with AI and machine learning frameworks at scale PyTorch, DeepSpeed, Megatron-LM, vLLM).
• Contributions to open-source infrastructure or ML tooling projects.
• Experience with large language model (LLM) training and inference infrastructure.

What We can offer You:

• Holiday purchase
• Private medical
• Income protection
• Attractive pension scheme
• Positive work life balance
• Learning and development
• Hybrid working model (3:2)
• Life insurance
• Lenovo and Motorola products discounts
• Lifestyle discounts
• Cycle to many more!