At a Glance
- Tasks: Build and operate AI capabilities for a global software platform.
- Company: Join a multi-billion dollar software conglomerate with a remote-first culture.
- Benefits: Enjoy competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with a focus on innovation and measurable AI performance.
- Why this job: Make a real impact by shipping AI solutions that work in production, not just demos.
- Qualifications: Experience with AI systems, strong software engineering skills, and a collaborative mindset.
The predicted salary is between 67500 - 82500 £ per year.
Applied AI Engineer
Inviso is partnering with one of our clients to find an experienced Backend / Platform Engineer to join their team working remotely.
Inviso is managing the recruitment and placement process for this opportunity.
This is a remote, direct-hire permanent employee position for our client that is a global multi-billion dollar software conglomerate.
The Applied AI Engineer is responsible for building and operating AI capabilities across an enterprise platform, including agent runtimes, model routing, RAG, tool/function calling, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls.
This role is focused on shipping AI that works in production, not demos.
The ideal candidate understands how to move from prototype to monitored production systems, can evaluate AI behavior rigorously, and can partner with product and engineering teams to decide when AI is the right solution and when it is not.
Experience & Skills Required
- Experience shipping software backed by LLMs, ML models, RAG systems, or agentic workflows to real production users.
- Experience designing or implementing agent runtime, orchestration, model routing, tool/function calling, or AI workflow patterns.
- Strong understanding of RAG, grounding, retrieval quality, prompt design, context management, and evaluation approaches.
- Experience building evaluation harnesses, golden sets, regression checks, quality gates, or measurable AI performance frameworks.
- Ability to treat cost, latency, reliability, and safety as first-class engineering constraints.
- Experience building guardrails and controls for AI systems, including untrusted retrieved content, tool output risk, and failure modes.
- Experience monitoring production AI behavior and improving systems based on evidence, not opinion.
- Strong software engineering skills and ability to collaborate with backend, platform, product, and security teams.
- Strong communication and collaboration skills for client-facing consulting environments.
- Pragmatic mindset with the ability to prioritize business value and ship useful AI capabilities quickly and responsibly.
- Desired Qualifications
- Experience with Claude, GPT, Azure Open AI, open-source models, model routing, fine-tuning, distillation, or small/edge models.
- Experience with MCP, A2A, multi-agent orchestration, AI tool calling, or agent evaluation.
- Experience with LLM-as-judge approaches calibrated against human evaluation.
- Experience with semantic knowledge management, ontologies, knowledge graphs, or semantic layers.
- Experience with AI development lifecycle practices across data, build, evaluation, deployment, monitoring, and continuous improvement.
- Experience using AI-assisted development tools while maintaining strong review, testing, and safety discipline.
- Success Criteria
Success in this role is measured by the ability to deliver AI capabilities that are useful, reliable, measurable, safe, and cost aware.
Applied AI Engineers are expected to turn experiments into production features, build evaluation discipline into the delivery process, and help client teams make informed decisions about where AI creates real value.
Applied AI Engineer - United Kingdom employer: Inviso
Inviso provides a supportive work culture that values innovation and collaboration. Employees benefit from remote work options and the opportunity to engage with advanced technologies in their projects. The company is committed to fostering professional growth and development for its team members.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer - United Kingdom
✨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 Inviso 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 Inviso.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Inviso.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Inviso that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Applied AI Engineer - United Kingdom
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 Inviso.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Inviso 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 Inviso
✨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 Inviso 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.
