At a Glance
- Tasks: Lead the design and delivery of impactful AI projects that enhance customer experiences.
- Company: Join a forward-thinking tech company focused on innovative AI solutions.
- Benefits: Competitive salary, high autonomy, and the chance to shape AI strategies.
- Other info: Collaborative culture that values diversity, continuous learning, and innovation.
- Why this job: Make a real difference by building AI systems that empower small businesses.
- Qualifications: Extensive software engineering experience with strong leadership and AI expertise.
The predicted salary is between 80100 - 97900 £ per year.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer based in the United Kingdom. As a Staff AI Engineer, you will play a key role in shaping and delivering high-impact AI initiatives, building production-ready solutions that directly improve customer experiences. You will provide technical leadership across engineering teams, influence major architectural decisions, and help define the future of the organization's AI capabilities. Working within a collaborative, cross-functional environment, you will lead projects from initial design through production deployment. You will also strengthen the shared AI platform, establishing robust evaluation frameworks, quality standards, and scalable infrastructure. This is an opportunity to combine hands-on engineering with strategic influence, building reliable AI systems that deliver measurable value to real users.
Accountabilities
- Lead the technical design, development, and delivery of major AI initiatives, including AI-powered assistants, contextual data systems, and generative AI features.
- Contribute directly to production AI systems from the outset, identifying technical opportunities and delivering improvements to existing architecture and workflows.
- Drive early improvements in AI quality, reliability, and performance by addressing known failure points, strengthening evaluation coverage, and implementing measurable enhancements.
- Take ownership of major AI projects from architecture and technical planning through cross-functional collaboration, deployment, and ongoing optimization.
- Define and influence architectural decisions across engineering teams, with particular responsibility for AI architecture and shared platform infrastructure.
- Establish scalable AI quality frameworks, including automated evaluations, regression testing, guardrails, agent tracing, human feedback mechanisms, and production monitoring.
- Design and implement reliable AI agents and tool integrations, balancing deterministic code and LLM capabilities while addressing security, latency, reliability, and cost.
- Drive broader engineering initiatives that improve development quality and velocity, such as AI evaluation standards, agentic software development practices, code review processes, and technical documentation.
- Collaborate closely with Product, Design, QA, Operations, and engineering stakeholders to translate business needs into effective technical solutions.
- Promote engineering excellence through technical mentorship, knowledge sharing, clear architectural standards, and a culture of continuous improvement.
Requirements
- Extensive experience in software engineering at Staff Engineer or equivalent level, with a proven ability to lead complex, ambiguous initiatives as a hands-on individual contributor.
- Demonstrated experience designing, building, and deploying production-grade LLM applications, AI agents, or generative AI features used by real customers.
- Strong technical leadership skills, including the ability to influence architectural decisions across teams, establish engineering standards, and drive initiatives from proposal through implementation.
- Proven experience building and maintaining AI evaluation frameworks that combine automated testing, agent traces, human feedback, and production monitoring to measure quality and prevent regressions.
- Strong understanding of AI agent architecture, tool design, and orchestration, including the ability to determine when deterministic logic is preferable to LLM-based solutions.
- Experience designing secure and reliable tool boundaries, human-in-the-loop workflows, and systems that balance performance, latency, security, and operational costs.
- Sound judgment in build-versus-buy decisions, model selection, and AI provider integrations.
- Strong backend and platform engineering expertise, particularly with Python and Django, PostgreSQL, Redis, asynchronous workers, and REST or GraphQL APIs.
- Ability to design scalable shared AI infrastructure with well-defined interfaces, efficient caching strategies, and robust tenant isolation.
- Excellent problem-solving, communication, and collaboration skills, with the ability to work effectively across Product, Design, QA, and engineering teams.
- A pragmatic, measurement-driven approach to AI development, prioritising evidence, evaluation, and reliability over simply changing models or rewriting prompts.
Benefits
- Competitive salary package.
- Opportunity to build and ship production AI solutions used daily by real customers.
- Broad technical scope across multiple AI products and the shared infrastructure supporting them.
- Significant architectural influence and participation in major technical decision-making processes.
- Access to a valuable proprietary dataset drawn from approximately 1,200 aesthetic medical practices, supporting the development of differentiated AI capabilities.
- High-autonomy, high-ownership Staff-level individual contributor role with direct influence over the AI roadmap and engineering strategy.
- Opportunity to contribute to meaningful technology that empowers independent business owners and supports the long-term growth of small businesses.
- Collaborative, inclusive, and ownership-driven engineering culture that values speed, care, continuous learning, and simplicity.
- A workplace that welcomes diverse backgrounds and perspectives, with accommodations available throughout the recruitment process.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analysing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Staff AI Engineer employer: Jobgether
As a Senior ML Engineer at our innovative healthcare-focused company in the UK, you will be part of a dynamic team dedicated to transforming clinical environments through cutting-edge technology. We offer a collaborative work culture that fosters creativity and professional growth, alongside competitive benefits and opportunities for continuous learning in the rapidly evolving field of machine learning. Join us to make a meaningful impact on healthcare while enjoying a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Staff AI Engineer
✨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 Jobgether 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 Jobgether.
✨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 Jobgether.
✨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 Jobgether 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 Staff AI Engineer
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 Jobgether.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Jobgether 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 Jobgether
✨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 Jobgether 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.