At a Glance
- Tasks: Build and deploy cutting-edge AI systems for defence and national security.
- Company: Fast-growing tech company focused on innovative AI solutions.
- Benefits: Rapid career progression, flexible hours, hybrid working, and private healthcare.
- Other info: Join a dynamic team and shape the future of AI technology.
- Why this job: Make a real impact in AI while enjoying ownership and purpose.
- Qualifications: Active SC clearance and experience with multi-agent AI systems.
The predicted salary is between 60000 - 80000 £ per year.
Must hold SC or DV Clearance. Experience, qualification, and soft skills, have you got everything required to succeed in this opportunity? Find out below.
Permanent (may consider Contractors). You will work closely with the entire team. You will be trusted with judgment calls. You will influence the business. And you will see the impact of your work every day. If you are excited by ownership, pace and purpose - and by building something that genuinely matters - we would love to hear from you.
What You Will Be Doing
We are looking for AI engineers who build and ship agentic AI systems in production. You will work at the cutting edge of agentic and generative AI - designing multi-agent pipelines, integrating large language models and vision-language models into real workflows, and deploying them into secure and air-gapped environments for defence and national security customers. This is a delivery role. You will own features end-to-end - from design through to deployment in constrained environments where reliability and security matter more than speed to market.
Key Responsibilities
- Architect, build, and optimise multi-agent AI systems using frameworks such as LangGraph, Haystack, or equivalent.
- Integrate LLMs and vision-language models into agent workflows for reasoning, search, summarisation, and task execution.
- Deploy AI systems into cloud, on-premises, and air-gapped environments.
- Build production-ready pipelines from data ingestion through to inference.
- Experience with observability for AI systems, including agent behaviour, model performance, and failure modes.
- Collaborate with engineers, product leads, and customers to translate requirements into working systems.
- Contribute to evaluation frameworks, system integration, and performance tracking.
- Act as a technical authority for agentic AI - setting design patterns for junior engineers.
Requirements
- Active SC clearance.
- Commercial experience building multi-agent or agentic AI systems in production.
- Strong Python skills and hands-on experience with LLM frameworks (LangGraph, LangChain, Haystack, or similar).
- Experience deploying AI/ML systems into production environments.
- Familiarity with Docker, Git, and cloud platforms (AWS preferred).
- Understanding of secure deployment patterns - air-gapped, on-premises, or sovereign cloud.
Preferred
- Experience with multimodal reasoning.
- Experience with edge or offline AI deployments.
- Familiarity with Kubernetes (EKS/OpenShift) for monitoring and managing deployed applications.
- MLOps experience - model evaluation, monitoring, reproducibility.
- Observability tooling for agentic systems (model drift, agent behaviour, performance monitoring).
- Experience with agent orchestration patterns and inter-agent communication protocols (e.g. A2A).
- Familiarity with MCPs for tool and context integration in agentic systems.
- Familiarity with secure-by-design development principles (ISO 27001, NIST, OWASP).
- Experience in defence, national security, or similarly regulated environments.
- Contributions to open-source AI/ML projects.
Soft Skills
- Delivery-focused - you ship working systems, not prototypes.
- Comfortable operating across the stack when needed.
- Strong communicator - can present to technical and non-technical stakeholders.
- Thrives in small teams with high ownership.
Benefits include:
- Rapid career progression and personal growth.
- Flexible working hours.
- Opportunity to shape the future of a fast-growing business.
- Hybrid working model.
- Company pension (NEST) with 4% employer contribution.
- Private Healthcare.
AI Engineer in Upton employer: MarkIT Placements
Contact Detail:
MarkIT Placements Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in Upton
✨Tip Number 1
Network like a pro! Reach out to current employees or connections in the industry. A friendly chat can give you insider info and might even lead to a referral, which is always a bonus!
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can talk confidently about your experience with AI systems and frameworks like LangGraph or Haystack. We want to see your passion shine through!
✨Tip Number 3
Showcase your projects! If you've built any AI systems or contributed to open-source projects, make sure to highlight them. We love seeing real-world applications of your skills, especially in secure environments.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you’re genuinely interested in being part of our team.
We think you need these skills to ace AI Engineer in Upton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with multi-agent systems and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of your work, especially those involving LLM frameworks or secure deployments. We love seeing real-world applications of your skills, so don’t hold back on the details!
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. We appreciate straightforward communication, so make sure you express your enthusiasm for the role and how you can contribute to our team.
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’s super easy!
How to prepare for a job interview at MarkIT Placements
✨Know Your Tech Inside Out
Make sure you’re well-versed in the frameworks mentioned in the job description, like LangGraph and Haystack. Brush up on your Python skills and be ready to discuss how you've used these tools in real-world projects.
✨Showcase Your Security Savvy
Since this role requires SC or DV clearance, be prepared to talk about your experience with secure deployment patterns. Highlight any past work in air-gapped or on-premises environments to demonstrate your understanding of security protocols.
✨Communicate Clearly and Confidently
You’ll need to present ideas to both technical and non-technical stakeholders, so practice explaining complex concepts in simple terms. Use examples from your past experiences to illustrate your points and show how you can bridge the gap between teams.
✨Emphasise Your Delivery Focus
This is a delivery role, so be ready to discuss how you’ve owned features from design to deployment. Share specific examples of how you’ve shipped working systems and the impact they had, especially in high-stakes environments like defence or national security.