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- Tasks: Design and build AI systems that enhance public services and decision-making.
- Company: Join a tech consultancy focused on impactful AI solutions for clients.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real difference by integrating cutting-edge AI into essential public services.
- Qualifications: Strong Python skills and experience with AI models and production environments.
- Other info: Collaborative teams and a focus on ethical AI practices.
The predicted salary is between 28800 - 48000 £ per year.
Are you an AI engineer who loves taking models out of the lab and putting them into real, high-impact production systems? Do you want to build secure, responsible AI solutions that genuinely improve public services and decision-making? Are you excited by integrating cutting-edge AI into complex platforms—while working in environments that value ethics, governance, and quality?
We are seeking an AI Engineer to design, build, and operate AI-powered systems that support the delivery of critical public services. You will work within multidisciplinary teams to implement reliable, secure, and governable AI capabilities within government digital services. The role focuses on applying modern AI models and platforms to real-world use cases, improving decision-making, automating workflows, and enhancing user experience across public-sector systems. This role is suited to an engineer who enjoys shipping AI into production, integrating AI into existing services, and working within strong ethical, security, and governance constraints.
Key ResponsibilitiesAs an AI Engineer, you will:
- Design and build AI-enabled services and workflows for public-sector use cases
- Develop production-ready AI services using Python and modern AI frameworks and APIs
- Build and operate AI-powered agents and automation, with appropriate controls, monitoring, and human oversight
- Integrate language and multimodal models (e.g. text, documents, images) into digital services and APIs
- Embed AI capabilities directly into products and services (e.g. decision support, case handling, internal tools), rather than standalone chatbots
- Build and maintain data flows required for AI inference, evaluation, and monitoring
- Optimise AI systems for reliability, latency, and cost-effective inference
- Monitor live AI systems for quality, drift, bias, and operational failure modes
- Apply responsible AI principles, including explainability, auditability, and governance standards
- Collaborate closely with product managers, designers, data professionals, and software engineers
- Contribute to documentation, code reviews, and shared AI tooling and standards
You will bring:
- Strong experience using Python to build production services and AI-enabled applications
- Hands-on experience integrating large language models and AI APIs into real systems
- Experience deploying and operating AI services in production environments
- Understanding of AI operations (monitoring, evaluation, versioning, and rollback)
- Experience integrating AI capabilities into APIs, workflows, and digital platforms
- Familiarity with cloud platforms (AWS, Azure, or GCP) and managed AI services
- Solid engineering fundamentals (testing, CI/CD, observability, security)
- Experience working in regulated, secure, or high-compliance environments
- Strong communication skills and comfort working in multidisciplinary teams
Ideally, you’ll also have:
- Experience in public sector, healthcare, defence, or government environments
- Experience building agent-based systems, orchestration, or workflow automation
- Knowledge of AI governance, assurance, and audit requirements
- Experience with explainability, evaluation, and bias monitoring for AI systems
- Familiarity with open-source AI tooling and modern inference frameworks
- Experience contributing to shared platforms or internal AI enablement teams
About usesynergy: usesynergy is a technology consultancy and we build products, platforms and services to accelerate value for our clients. We drive measurable impact that is tightly aligned to our clients’ business objectives. Put in practice that means high transparency, metric-driven reporting, and incremental handovers and a consistent focus on building our clients’ capability. Our delivery teams are small and highly functional, formed by a vetted ecosystem of associates, luminaries and partners. We choose technologies that are the right fit for our clients’ needs and are not opinionated around specific tech stacks and service offerings.
AI Engineer in London employer: Synergy Solutions Limited
Contact Detail:
Synergy Solutions Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI field. Attend meetups, webinars, or conferences where you can chat with industry experts and potential employers. Remember, sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that demonstrate your ability to integrate models into real-world applications. This will give you an edge and show employers that you can deliver results.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, AI frameworks, and how you've tackled challenges in previous roles. Practice makes perfect, so consider mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented AI engineers who are passionate about making a difference. Your next big opportunity could be just a click away, so get your application in and let’s make some impact together!
We think you need these skills to ace AI Engineer in London
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI shine through! We want to see how excited you are about taking models from the lab to real-world applications, especially in public services. Share any relevant projects or experiences that highlight your love for building impactful AI solutions.
Tailor Your Application: Make sure to customise your application to match the job description. Highlight your experience with Python and AI frameworks, and don’t forget to mention any work you've done in regulated environments. We appreciate candidates who take the time to align their skills with what we’re looking for!
Be Clear and Concise: Keep your application straightforward and to the point. We value clarity, so avoid jargon and focus on communicating your skills and experiences effectively. Use bullet points if it helps to make your achievements stand out—this makes it easier for us to see what you bring to the table!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us that you’re genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at Synergy Solutions Limited
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI models and frameworks, especially those relevant to the public sector. Be ready to discuss how you've applied Python in production environments and integrated AI APIs into real systems.
✨Showcase Your Ethical Side
Since this role emphasises ethics and governance, prepare examples that demonstrate your understanding of responsible AI principles. Talk about how you've ensured explainability and auditability in your past projects.
✨Collaborate Like a Pro
This position involves working with multidisciplinary teams, so be ready to share experiences where you successfully collaborated with product managers, designers, and other engineers. Highlight your communication skills and how they helped in achieving project goals.
✨Prepare for Real-World Scenarios
Think of specific use cases where you've designed or built AI-enabled services. Be prepared to discuss challenges you faced in deploying AI in production and how you monitored and optimised these systems for reliability and performance.
