At a Glance
- Tasks: Develop and enhance AI agents for real customer needs using cutting-edge technologies.
- Company: Join WorkWave, a leader in innovative AI solutions with a collaborative remote culture.
- Benefits: Enjoy a competitive salary, health benefits, and opportunities for professional growth.
- Other info: Be part of a dynamic team focused on improving user experience and agent performance.
- Why this job: Make a tangible impact on AI technology while working remotely in the UK.
- Qualifications: 5+ years in software development, strong Python skills, and experience with AWS.
The predicted salary is between 63000 - 77000 £ per year.
WorkWave is hiring a Senior AI Engineer for its Agentic Platform team in a remote UK role. The position is full-time and focuses on production agents, evaluation systems, retrieval, tool use, and customer-facing outcomes. The engineer owns agent work from a customer need through delivery and iteration. The role requires the legal right to work in the UK, and WorkWave does not provide visa sponsorship.
The engineer works with Amazon Bedrock, Bedrock AgentCore, MCP, Python, service APIs, semantic layers, and business data. WorkWave's AskWaive assistant is already live, so the role centres on improving quality, coverage, explanations, and user experience in a production setting. The team also operates the serving path and measures adoption, task success, feedback, latency, response cost, and runtime failures.
Agent Outcomes And Production Delivery
The engineer owns agent outcomes from the initial customer need through delivery and iteration. Production work includes retrieval, multi-step workflows, action-taking, tool and function design, context assembly, and service integration. Semantic-layer and service-API capabilities become agent endpoints and tools that support real customer tasks. Agent behaviour remains a product concern as well as an engineering concern. The role considers when a system should answer, ask for more information, or refuse, and how it should explain its work. Measurement covers adoption, feedback, intent, task success, decision quality, and customer impact, with findings reported to Product and the wider business.
Evaluation Harnesses And Regression Gates
- Labelled test sets for repeatable agent checks
- Groundedness and hallucination measures
- Regression gates in continuous integration
- Execution tracing and failure diagnosis
- Feedback and intent measures connected to customer impact
Experience with generative-system evaluation, defensible measures, and verification of coding-agent output matches the role's stated technical scope. Strong SQL and metric fluency support the analysis of business data and agent performance.
AWS Runtime And Service APIs
Amazon Bedrock and Bedrock AgentCore are named technologies for the role, while equivalent agent runtimes provide transferable experience. The serving path includes MCP endpoints, latency, response cost, caching, and runtime guardrails. The engineer also drives data or infrastructure changes when existing services limit agent capabilities. Strong Python skills support the implementation work, and hands-on AWS experience supports deployment and operation. Retrieval over business data requires an explanation of context selection and answer failures, while typed interfaces, tests, and verification harnesses keep changes dependable.
WorkWave's AI And Data Team
WorkWave's AI and Data Analytics team works on AskWaive, an in-product assistant that is already used in the product. The role builds on the company's core data platform while working with Product Managers and engineers across technical and non-technical areas. The role also includes operating discipline after release. Instrumentation, tracing, caching, runtime cost, and guardrails remain part of the serving work, and the engineer reports measurable findings to the business.
Experience in field service, logistics, operational software, observability, semantic layers, or technical leadership is listed as a bonus. Five or more years building production software or data-intensive systems for customers forms the main experience threshold. A shipped LLM or agent feature, AWS work, and strong communication complete the central profile, while senior or lead engineering experience can extend the role's technical direction.
The successful engineer enters a team where agent quality is tested against labelled evidence and production behaviour. The position combines implementation, measurement, customer impact analysis, and platform operation within a UK remote working arrangement. The AI jobs category includes roles connected with production AI systems and software delivery. UK AI providers represent the wider professional setting in which this work takes place.
Senior AI Engineer: WorkWave employer: UK AI Tools & Digital Services
UK AI Tools & Digital Services provides a flexible and collaborative work environment, allowing employees to engage in meaningful projects that enhance their skills. The focus on innovation and quality ensures that team members contribute to impactful AI solutions. With opportunities for professional development, the company supports career growth in the rapidly evolving tech landscape.
Contact Details:
UK AI Tools & Digital Services Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer: WorkWave
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We think you need these skills to ace Senior AI Engineer: WorkWave
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 UK AI Tools & Digital Services.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at UK AI Tools & Digital Services 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 UK AI Tools & Digital Services
✨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 UK AI Tools & Digital Services 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.
