At a Glance
- Tasks: Design and evolve cutting-edge multi-agent systems and build innovative AI solutions.
- Company: Join a pioneering AI-first analytics startup in Central London.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with mentorship opportunities and exciting projects.
- Why this job: Make a real impact in AI engineering and shape the future of agentic systems.
- Qualifications: 3-5 years in software engineering with strong Python and LLM experience.
The predicted salary is between 80100 - 97900 £ per year.
We’re hiring on behalf of an AI-first analytics startup whose product runs on a production multi-agent system: Anthropic, OpenAI and Perplexity models orchestrated on AWS, and exposed to customers through the company’s own MCP server. This is a real AI engineering role, not calling an API from a web app. The platform already has real users. The job is deciding what good looks like and building the agents, evals and infrastructure that get it there, while setting the technical bar for the team.
What you’ll do:
- Design and evolve multi-agent systems: agent topologies, tool calling, memory and context management, and the agent harness itself
- Extend the company’s MCP server with new tools and capabilities
- Build the eval and observability layer: golden datasets, regression suites, LLM-as-judge, and cost and latency tracking per model and client
- Own the AWS infrastructure behind it (ECS Fargate, Lambda, Step Functions, S3, DynamoDB, Bedrock), plus CI/CD and infrastructure as code
- Guard against prompt injection, PII leakage and cross-tenant data access
- Set technical direction, make build-vs-buy calls and mentor other engineers
What we’re looking for:
- 3–5 years of software engineering, including 2+ years shipping LLM or GenAI systems in production
- Strong Python, and hands-on experience with an agent framework (LangGraph, Strands, CrewAI, OpenAI Agents SDK, Claude Agent SDK or similar)
- Production use of LLM APIs, including tool calling and structured outputs, plus RAG (embeddings, vector stores, reranking)
- Experience building LLM evals and observability
- Solid AWS, and system design for distributed, event-driven systems
- A bonus: MCP servers or tools, multi-tenant AI systems, cost optimisation across LLM providers, open-source AI contributions
- Right to work in the UK is a must
If you use AI agents in your own workflow and have strong opinions on how agentic systems should be built, we’d like to hear from you.
AI Engineer employer: Hyre Ai
Hyre AI is an exceptional employer, offering a dynamic work environment where innovation meets purpose in the fast-paced world of cybersecurity. As a Senior Software Engineer, you'll not only contribute to cutting-edge technology but also enjoy stock options and the chance to shape a category-defining product alongside a high-calibre team in London. With a culture that values ownership, collaboration, and thoughtful experimentation, this is a unique opportunity for meaningful growth and impactful engineering work.
StudySmarter Expert Advice🤫
We think this is how you could land 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 Hyre Ai 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 Hyre Ai.
✨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 Hyre Ai.
✨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 Hyre Ai 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 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 Hyre Ai.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Hyre Ai 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 Hyre Ai
✨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 Hyre Ai 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.
