At a Glance
- Tasks: Design and build innovative AI solutions using NVIDIA technology for enterprise clients.
- Company: Join a leading tech firm at the forefront of AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement opportunities in a fast-paced environment.
- Why this job: Make a real impact by solving complex business challenges with cutting-edge AI.
- Qualifications: Master's degree in relevant fields and strong experience with NVIDIA products required.
We are currently looking to recruit an NVIDIA Engineer to design, prototype, and deliver NVIDIA-enabled AI solutions that demonstrate measurable value for enterprise and public-sector clients. The role will accelerate innovation by translating complex business challenges into secure, scalable proofs of concept, reusable accelerators, and production-ready deployment patterns.
Role Summary
We are seeking an NVIDIA Engineer to design and build prototypes, proofs of concept, and production-ready accelerators for large enterprise and public-sector clients. The role requires hands-on experience with NVIDIA’s AI stack, agentic AI frameworks, and enterprise deployment practices, with the ability to translate client problems into working technical demonstrations and scalable solutions.
Key Responsibilities
- Design and build AI use cases and POCs for strategic clients.
- Prototype agentic workflows, copilots, and automation solutions.
- Develop and optimize inference pipelines for large language models and multimodal AI.
- Build secure, governed, enterprise-ready AI demos and pilots.
- Work closely with the AI Director, solution architects, and delivery teams to shape technical proposals.
- Create reusable accelerators, blueprints, and reference implementations.
- Present technical solutions to client stakeholders and senior leadership.
- Support R&D experiments, benchmarking, and platform evaluations.
- Contribute to deployment patterns for cloud, sovereign cloud, and hybrid environments.
- Ensure safe and responsible AI design with guardrails, evaluation, and observability.
Required NVIDIA Skills
- Candidates should have practical experience or strong working knowledge of the following NVIDIA products and frameworks, grouped by capability.
- Infrastructure Runtime & Inference Optimization
- TensorRT-LLM, TensorRT, Triton Inference Server.
- CUDA-X Data Science, including cuDF and RAPIDS.
- Microservices & Agentic AI Frameworks
- NeMo Guardrails and NVIDIA NeMo Customizer.
Core Foundational Language & Vision Models
- Nemotron models, including enterprise-grade reasoning and tool-calling use cases.
- Cosmos for multimodal and physical AI scenarios.
- Experience using foundation models in agentic or retrieval-based workflows.
- cuOpt.
- NVIDIA Metropolis Microservices.
- Riva.
- NVIDIA ACE.
- Physical AI, Robotics & Digital Twins
- Omniverse / USD Composer.
- Isaac GR00T.
- Edge and local inference deployment concepts for industrial or physical environments.
Technical Skills
- Experience with LLM application development.
- API integration and workflow automation.
- RAG architecture and document intelligence.
- Containerization with Docker and Kubernetes.
- Familiarity with cloud platforms, especially Azure.
- Experience with Git, CI/CD, and production deployment.
- Ability to create demos, POCs, and technical artifacts quickly.
- Good understanding of data preparation, evaluation, and observability.
Domain Experience
- Government and public services.
- Financial services, including investment banking or hedge funds.
- Pharmaceuticals, life sciences, or healthcare.
- Enterprise operations, shared services, or regulated industries.
Personal Attributes
- Strong problem-solving ability.
- Comfortable working in ambiguity.
- Fast prototyping mindset.
- Client-focused and commercially aware.
- Able to balance experimentation with production discipline.
About the Environment
- This role sits at the intersection of AI engineering, client advisory, and solution development. The engineer will help the business move from idea to demonstrable value by using NVIDIA’s enterprise AI stack to build practical, secure, and scalable AI solutions.
Must-have qualifications
- Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- NVIDIA certification is mandatory. Candidates must hold at least one current NVIDIA credential relevant to generative AI, agentic AI, or AI infrastructure.
- Proven ability to build AI use cases, prototypes, and POCs for large enterprise clients.
- Strong experience using NVIDIA AI products and frameworks for production-grade solution development.
Person Specification
- Strong leadership, organisational and problem-solving skills with the ability to lead delivery in ambiguous, fast-moving client environments.
- Comfortable balancing hands-on technical depth with senior stakeholder communication, facilitation and decision‑making.
- Strong presentation, stakeholder management and client‑facing delivery skills, with the credibility to work across engineering and business audiences.
- Strong Azure skills are required, including experience with Azure AI services, Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Machine Learning, Azure Functions, Azure App Service, Azure Container Apps or AKS, and core Azure data and integration services.
- Experience delivering production‑grade AI and data solutions on Azure, including security, observability, performance tuning, deployment practices and operational support.
- Ability to prototype rapidly in Python and/or C#, work with APIs and SDKs, and translate business requirements into scalable Azure solution designs.
- Knowledge of responsible AI, governance, security and production monitoring practices for Azure AI workloads.
- Business analysis, solution design and forward deployment engineering capabilities, with a focus on measurable customer outcomes and adoption.
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NVIDIA Engineer in London employer: Bell Integration
At Bell Integration, we pride ourselves on being a people-first employer that values employee experience and development. Our collaborative work culture fosters innovation and inclusivity, while our commitment to AI-driven processes ensures efficiency and accuracy in all operations. With opportunities for growth and a supportive environment, joining us as a People Advisor means becoming part of a dynamic team dedicated to making a positive impact across our global workforce.
StudySmarter Expert Advice🤫
We think this is how you could land NVIDIA Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Bell Integration or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Bell Integration.
✨Tap into Online Developer Communities
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We think you need these skills to ace NVIDIA Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Bell Integration.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Bell Integration and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Bell Integration
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Bell Integration uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
