Senior AI Platform Engineer

IQVIA Argentina; Greater London; On-site; GBP 100,000 - 160,000; Full time

Job summary

IQVIA is seeking a Senior AI Platform Engineer to define and deliver the infrastructure strategy underpinning its LLM programmes. You will provide technical leadership across compute, data, model lifecycle management, and platform engineering, ensuring research innovations can be transformed into secure, scalable, production-ready AI solutions.

You will partner with research, product, infrastructure, data engineering and MLOps teams to design and operate the platforms required to train,

Qualifications

• Significant experience designing, building, and operating large-scale AI platforms in enterprise environments.
• Deep understanding of LLM architectures and GPU interaction (CUDA, cuDNN, NCCL, etc.).
• Knowledge of distributed training and inference strategies (tensor/pipeline/data/expert parallelism).
• Experience optimising LLM inference workloads with high-performance serving frameworks.

Responsibilities

• Own the AI platform and infrastructure roadmap for LLM initiatives and translate research requirements into scalable engineering solutions.
• Partner with centralised infrastructure teams to design high-performance compute environments across AWS and on‑premises, including GPU infrastructure and Slurm clusters.
• Optimise LLM training and inference workloads for performance, scalability, and reliability across the stack.
• Establish and maintain model and data lifecycle capabilities and integration with model registries.
• Lead evolution of knowledge graph infrastructure and integration with AI workflows.
• Coordinate across AI Research, Data Engineering, MLOps, Product, and Infrastructure to resolve dependencies.
• Provide leadership for vendor selection and technology partnerships (compute architectures, GPUs, AI platforms).
• Define platform engineering standards, governance, and best practices while mentoring engineers.

Skills

AI platform design

LLM architectures

GPU infrastructure

AWS cloud

Distributed training

Inference optimisation

Model lifecycle

Cross-functional leadership

Governance & security

Tools

Slurm

Kubernetes

Ray

TensorRT

NVIDIA Nsight

CUDA

NVIDIA NCCL

Job description

Senior AI Platform Engineer

The Senior AI Platform Engineer is responsible for defining and delivering the infrastructure strategy underpinning IQVIA's 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.

It's an exciting time to join and reimagine what's 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 https://jobs.iqvia.com

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.