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For Companies At a Glance
- Tasks: Design and deploy cutting-edge AI systems that make a real-world impact.
- Company: Join a fast-moving team at the forefront of applied AI.
- Benefits: Competitive salary, bonuses, remote work, and opportunities for growth.
- Why this job: Be part of innovative projects that shape the future of AI technology.
- Qualifications: Experience in building LLM/agentic systems and strong software engineering skills.
- Other info: Remote-first role with international collaboration and excellent career advancement.
The predicted salary is between 54000 - 84000 £ per year.
📍 Liverpool | Hybrid: 2-3 days on-site + client travel
This is not a theoretical or demo-driven AI role. We’re hiring engineers who design, deploy, and scale agentic AI systems in production. You’ll partner directly with enterprise and public-sector clients, taking initiatives from early proof-of-concept through to mission-critical platforms used by hundreds or thousands of users.
If you enjoy operating at the intersection of deep engineering, real-world delivery, and client impact, this role was built for you.
What You’ll Be Responsible For
- Architect agentic AI systems – Design and own full agent lifecycles (plan → act → reflect), orchestration layers (DAGs, state machines), and memory strategies.
- Build production-grade tooling – Implement schemas, safety controls, retries, rate limiting, and extensible SDKs.
- Develop memory & retrieval services – Create episodic and semantic memory pipelines, RAG APIs, deduplication, and summarisation agents.
- Deploy at scale – Productionise systems using Kubernetes, serverless, GPU infrastructure, CI/CD pipelines, observability, and auto-scaling.
- Ensure reliability & governance – Apply guardrails, cost/latency controls, checkpointing, and critic/reviewer patterns.
- Evaluate and monitor – Build automated evaluation frameworks, golden datasets, retriever testing, and drift detection.
- Work with clients – Lead technical workshops, delivery roadmaps, and AI maturity assessments, translating complexity into outcomes.
What We’re Looking For
- Hands-on experience shipping LLM or agentic AI systems into production.
- Strong software engineering fundamentals across orchestration, deployment, monitoring, and reliability.
- Experience with agentic architectures (e.g. LangGraph, ReAct, CoT loops) or building custom frameworks from first principles.
- Degree in Computer Science, AI, or related discipline.
- Experience with PyTorch or TensorFlow, vector databases, RAG pipelines, and orchestration platforms.
- Comfortable operating in client-facing delivery environments.
Nice to Have
- Background in consulting, scale-ups, or high-ownership start-up environments.
- Exposure to regulated or high-stakes industries.
- Self-directed, entrepreneurial mindset with a bias toward execution.
Why Join This Team?
- Real Impact – Deliver production-ready agentic AI systems solving real operational problems.
- Technical Depth – Work beyond “glue code” on orchestration, deployment, and system reliability.
- Global Exposure – Hybrid role with international client and team collaboration.
- Career Acceleration – Influence how enterprises adopt and scale agentic AI.
- Culture – Fast-moving, delivery-focused, and genuinely at the frontier of applied AI.
Keywords (SEO):
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Artificial Intelligence Engineer employer: Omnis Partners
Contact Detail:
Omnis Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, attend meetups, and join online forums. The more connections we make, the better our chances of landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving agentic AI systems. We want to see what you can do, so let’s make it easy for potential employers to be impressed.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI engineering. We should also be ready to discuss our past experiences and how they relate to the role. Confidence is key!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing familiar names when we’re reviewing candidates. Let’s get you in the door!
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI shine through! We want to see how you’ve engaged with the field, whether it’s through projects, research, or even personal interests. Make it clear why this role excites you!
Tailor Your Experience: Don’t just send a generic CV! Highlight your experience with agentic systems and any relevant projects you've worked on. We’re looking for specific examples that demonstrate your skills in building and deploying AI systems.
Be Clear and Concise: Keep your application straightforward and to the point. Use bullet points where possible to make it easy for us to read. We appreciate clarity, so avoid jargon unless it’s necessary to showcase your expertise.
Apply Through Our Website: Make sure to submit your application through our website! It’s the best way for us to keep track of your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Omnis Partners
✨Know Your AI Stuff
Make sure you brush up on your knowledge of agentic AI systems and architectures. Be ready to discuss your experience with LLMs, orchestration, and memory management. The more specific examples you can provide about your past projects, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled challenges in deploying AI systems. Think about times when you had to implement CI/CD or manage scaling issues. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Engage Like a Pro
Since this role involves client-facing interactions, practice how you would explain complex AI concepts in simple terms. You might even want to run through a mock workshop scenario with a friend to get comfortable with presenting your ideas.
✨Be Ready for Technical Questions
Expect some deep dives into your technical expertise. Brush up on your knowledge of tools like PyTorch, TensorFlow, and containerisation. Be prepared to discuss how you would build robust tooling and ensure system robustness in real-world applications.
