Senior AI Platform Engineer

Senior AI Platform Engineer

The Senior AI Platform Engineer is responsible for defining and delivering the infrastructure strategy underpinning IQVIAs Large Language Model (LLM) programmes. This role provides technical leadership across compute data model lifecycle management evaluation frameworks and platform engineering ensuring research innovations can be successfully transformed into secure scalable and production-ready AI solutions.

Acting as a key technical leader and cross-functional integrator the Senior AI Platform Engineer partners with research product infrastructure data engineering and MLOps teams to design and operate the platforms required to train evaluate deploy and govern large-scale AI systems across IQVIA products and healthcare use cases.

Key Responsibilities

• Own the AI platform and infrastructure roadmap leading the planning and execution of LLM initiatives and translating research requirements into scalable engineering solutions.
• Partner with centralised infrastructure teams to design and deliver high-performance compute environments across AWS and on-premises platforms including GPU infrastructure Slurm clusters and migration from ad hoc research workflows.
• Optimise LLM training and inference workloads supporting research and product teams in maximising performance scalability and reliability across the infrastructure stack.
• Establish and maintain model and data lifecycle capabilities including dataset versioning lineage tracking reproducibility standards and integration with model registries.
• Lead the evolution of knowledge graph infrastructure driving technology selection migration strategies performance optimisation and integration with AI workflows.
• Serve as the primary technical coordination point across AI Research Data Engineering MLOps Product and Infrastructure teams resolving dependencies and prioritising activities critical to delivery.
• Provide technical leadership for vendor selection procurement and technology partnerships advising on compute architectures GPU specifications AI platforms and integration approaches.
• Define platform engineering standards governance and best practices while mentoring engineers and promoting operational excellence across AI and platform teams.

Skills & Experience

• Significant experience designing building and operating large-scale AI machine learning or distributed computing platforms in enterprise environments.
• Deep understanding of LLM architectures and their interaction with GPU infrastructure including CUDA cuDNN NCCL kernel-level acceleration libraries and distributed training frameworks such as PyTorch.
• Strong knowledge of distributed training and inference strategies including tensor pipeline data and expert parallelism approaches.
• Experience optimising LLM inference workloads using technologies such as vLLM TensorRT-LLM NVIDIA NIM SGLang or similar high-performance serving frameworks.
• Expertise in model optimisation techniques including quantisation mixed precision training and inference (FP8 GPTQ AWQ LoRA) and performance tuning for large-scale model deployment.
• Advanced experience profiling troubleshooting and optimising GPU workloads using tools such as NVIDIA Nsight DCGM and related ecosystem technologies.
• Strong background in AWS cloud services high-performance computing distributed systems containerised environments and infrastructure automation.
• Experience with workload orchestration technologies such as Slurm Kubernetes Ray or equivalent distributed compute frameworks.
• Demonstrated success bridging research and production environments enabling rapid experimentation while maintaining operational excellence governance security and reliability.
• Proven ability to lead complex cross-functional initiatives influence technical direction and communicate effectively with engineering research product and executive stakeholders.

Why Join

Those who join us become part of a recognized global leader still willing to challenge the status quo to improve patient care. You will have access to the most cutting-edge technology the largest data sets the best analytics tools and in our opinion some of the finest minds in the Healthcare industry.

You can drive your career at IQVIA and choose the path that best defines your development and success. With exposure across diverse geographies capabilities and vast therapeutic and information and technology areas you can seek opportunities to change and grow without boundaries.

Regardless of your role we invite you to reimagine healthcare with us. You will have the opportunity to play an important part in helping our clients drive healthcare forward and ultimately improve human health outcomes.

Its an exciting time to join and reimagine whats possible in healthcare.

IQVIA is a strong advocate of diversity and inclusion in the workplace. We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success. We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees builds a stronger team and allows individual employees the opportunity to maximize their personal potential.

IQVIA is a leading global provider of clinical research services commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at

IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements misrepresentations or material omissions during the recruitment process will result in immediate disqualification of your application or termination of employment if discovered later in accordance with applicable law. We appreciate your honesty and professionalism.