NVIDIA AI Engineer

Franklin Fitch; Greater London; Hybrid; GBP 75,000 - 120,000; Full time

Job summary

Franklin Fitch is seeking an experienced NVIDIA AI Engineer to design and deliver innovative AI solutions for enterprise and public-sector clients. You will build proofs of concept, agentic workflows, copilots and production-ready accelerators, turning complex client challenges into secure and scalable solutions.

You should be comfortable combining hands-on engineering with client-facing work and moving quickly from an idea to a secure, demonstrable solution.

Qualifications

• Experience designing AI solutions for enterprise or public-sector clients.
• Hands-on engineering with client-facing delivery and rapid prototyping.
• Solid Python and LLM application-development skills.
• Experience with NVIDIA AI stack and cloud/hybrid deployments.
• At least one current NVIDIA certification.

Responsibilities

• Build AI prototypes, demonstrations and production solutions.
• Develop agentic AI, RAG and multimodal applications.
• Create reusable accelerators and deployment patterns.
• Present solutions to technical and senior business stakeholders.
• Support deployments across Azure, hybrid and sovereign-cloud environments.
• Apply AI security, governance and monitoring.

Skills

Python

LLM development

NVIDIA stack

APIs

Docker

Kubernetes

CI/CD

RAG

Tools

NIM

NeMo

TensorRT-LLM

Triton

AI Blueprints

Job description

We are looking for an experienced NVIDIA AI Engineer to design and deliver innovative AI solutions for enterprise and public-sector clients.

You will build proofs of concept, agentic workflows, copilots and production-ready accelerators, turning complex client challenges into secure and scalable solutions.

Key responsibilities:

• Build AI prototypes, demonstrations and production solutions.
• Develop agentic AI, RAG and multimodal applications.
• Create reusable accelerators and deployment patterns.
• Present solutions to technical and senior business stakeholders.
• Support deployments across Azure, hybrid and sovereign-cloud environments.
• Apply appropriate AI security, governance and monitoring.
• Strong Python and LLM application-development skills.
• Commercial experience with NVIDIA’s AI stack, such as NIM, NeMo, TensorRT-LLM, Triton or AI Blueprints.
• Experience with RAG, APIs, Docker, Kubernetes and CI/CD.
• A track record of delivering AI prototypes or solutions for enterprise clients.
• At least one current NVIDIA certification.

You should be comfortable combining hands-on engineering with client-facing work and able to move quickly from an initial idea to a secure, demonstrable solution.

Experience within government, financial services, healthcare, life sciences or another regulated sector would be beneficial.