At a Glance
- Tasks: Architect and build cutting-edge AI platforms and generative AI systems.
- Company: Join a leading tech group focused on innovative AI solutions.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with mentorship opportunities and significant technical influence.
- Why this job: Make a real impact in the AI field while working with top experts.
- Qualifications: Experience in AI Engineering and strong skills in Python and GCP.
The predicted salary is between 70000 - 90000 £ per year.
The Senior AI Engineer is a senior individual contributor responsible for architecting, building and scaling production‑grade AI platforms and generative AI systems across JD Group. Reporting into the Head of Data Science & AI, the role focuses on the engineering, operationalisation and governance of large‑scale AI solutions, including LLM‑based applications, agentic workflows and retrieval‑augmented generation systems. Working closely with Senior Data Scientists, Data Engineering, Platform and Product teams, the Senior AI Engineer ensures AI solutions are reliable, secure, cost‑effective and embedded into core business processes. This role carries significant technical leadership, mentorship and influence across the wider Data & AI community.
Responsibilities
- AI Platform & Solution Engineering
- Architect, develop and deploy enterprise‑scale AI and GenAI solutions including LLM applications, agentic workflows and tool‑using agents.
- Design, implement and optimise production‑grade RAG architectures with strong performance, scalability and latency characteristics.
- Build AI services, microservices, inference pipelines and platform components using modern engineering frameworks and patterns.
- Own technical decisions across AI system design, orchestration, routing, caching and runtime optimisation.
- Production Readiness, LLMOps & MLOps
- Define and implement standards for LLMOps, MLOps, monitoring, observability, safety and compliance.
- Ensure AI systems are robust, monitored, explainable and suitable for long‑term production use.
- Partner closely with Platform, DevOps and Security teams to deliver cloud‑native, secure and scalable solutions on GCP.
- Drive cost‑efficient AI deployment strategies including prompt optimisation, model selection, caching, distillation and compute optimisation.
- Governance, Risk & Responsible AI
- Embed responsible AI principles into system design, including safety, security, bias mitigation and data protection.
- Support governance frameworks for model usage, evaluation, auditability and risk management.
- Develop automated evaluation, testing and quality assurance frameworks for LLM‑based systems.
- Stakeholder Partnership & Influence
- Work closely with Senior Data Scientists to productionise AI‑driven analytical and decisioning solutions.
- Partner with Product, Engineering and Architecture leaders to shape AI solution design and delivery.
- Contribute to strategic decisions on AI infrastructure, architecture and long‑term platform roadmap.
- Evaluate and onboard AI vendors and third‑party platforms, prioritising buy‑first solutions where appropriate.
- Capability Building & Mentorship
- Provide technical mentorship and guidance to AI Engineers and adjacent engineering teams.
- Contribute to shared platforms, reusable components, reference architectures and best practices.
- Stay current with advances in generative AI, agentic systems and AI infrastructure, identifying pragmatic opportunities to apply new capabilities.
Role Objectives & KPIs
- Deliver production‑grade AI platforms and systems that generate measurable business value.
- Ensure AI solutions are scalable, reliable, secure and cost‑effective.
- Reduce operational risk through strong governance, automation and engineering standards.
- Successful end‑to‑end delivery of complex AI initiatives to agreed quality and timelines.
- Strengthen trust in AI as a decision‑making and operational capability.
- Strong stakeholder satisfaction and trust in AI delivery.
- Act as a senior technical role model within the Data Science & AI function.
Skills and Experience
- Significant experience in AI Engineering, ML Engineering or Software Engineering with proven production delivery.
- Deep expertise in LLMs, generative AI, agentic systems, RAG architectures and vector databases.
- Strong experience building distributed systems, microservices and scalable API‑driven platforms.
- Advanced experience with GCP AI stack (Vertex AI, BigQuery, Cloud Run, Cloud Functions, Cloud SQL, Agent Engine, AlloyDB etc.).
- Strong Python skills and experience building production‑grade AI services.
- Experience implementing LLMOps, MLOps, CI/CD and infrastructure automation.
- Expertise in developing applications with React, NextJS.
- Strong understanding of responsible AI, security, governance and data compliance.
- Ability to influence technical direction and communicate effectively with senior stakeholders.
- Experience in large‑scale, multi‑brand, or global enterprises; retail experience is advantageous.
- Delivery‑focused, pragmatic, and accountable.
- Line management/mentoring experience will be preferable.
Senior ai Engineer in Bury St Edmunds employer: JD GROUP
At JD Group, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior AI Engineer, you will have the opportunity to lead cutting-edge AI projects while benefiting from extensive mentorship and professional growth opportunities. Our commitment to responsible AI practices and a supportive environment ensures that your contributions will not only drive business success but also make a meaningful impact in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ai Engineer in Bury St Edmunds
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and generative AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and real-world applications. Be ready to discuss your experience with GCP, microservices, and production-grade AI solutions. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior ai Engineer in Bury St Edmunds
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior AI Engineer role. Highlight your experience with LLMs, generative AI, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for our team. Don't forget to mention any specific projects or achievements that showcase your expertise.
Showcase Your Technical Skills:In your application, be sure to highlight your technical skills, especially in Python, GCP, and building scalable systems. We love seeing concrete examples of how you've applied these skills in real-world scenarios, so don't hold back!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at JD GROUP
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, generative AI, and RAG architectures. Be ready to discuss specific projects you've worked on and how they relate to the role. This shows you're not just familiar with the concepts but have practical experience too.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles, especially around building scalable AI solutions. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you approached problems and what the outcomes were.
✨Understand the Business Impact
Be ready to discuss how your AI solutions can drive business value. Think about examples where your work has led to measurable improvements or efficiencies. This will demonstrate that you understand the bigger picture and can align technical decisions with business goals.
✨Engage with Stakeholders
Since this role involves working closely with various teams, prepare to discuss how you've successfully collaborated with stakeholders in the past. Highlight your communication skills and how you’ve influenced technical direction while ensuring everyone is on the same page.
