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About the Role
The Senior AI Platform Engineer defines and delivers the infrastructure strategy for IQVIA's Large Language Model (LLM) programs. This role provides technical leadership across compute, data, model lifecycle management, evaluation frameworks, and platform engineering to transform research innovations into secure, scalable, and production-ready AI solutions. The engineer partners with research, product, infrastructure, data engineering, and MLOps teams to design and operate platforms for training, evaluating, deploying, and governing large-scale AI systems.
Responsibilities
- Own the AI platform and infrastructure roadmap, leading LLM initiatives and translating research requirements into scalable engineering solutions.
- Partner with centralized infrastructure teams to design and deliver high-performance compute environments across AWS and on-premises platforms, including GPU infrastructure and Slurm clusters.
- Optimize LLM training and inference workloads to maximize performance, scalability, and reliability.
- 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 optimization, 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 prioritizing activities.
- 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.
Requirements
- Significant experience designing, building, and operating large-scale AI, machine learning, or distributed computing platforms in enterprise environments.
- 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.
Skills
- 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 optimizing LLM inference workloads using technologies such as vLLM, TensorRT-LLM, NVIDIA NIM, SGLang, or similar high-performance serving frameworks.
- Expertise in model optimization 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.
Location
- AWS
- on-premises
Work Type
- Full-time
Experience Level
- Senior
About the Company
- 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 https://jobs.iqvia.com
Equal Opportunity
- 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 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.