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- Tasks: Lead the design and build of cutting-edge AI systems for real-world applications.
- Company: Join LEC AI, a pioneering division of London Export Corporation focused on operational intelligence.
- Benefits: Enjoy a dynamic work environment with high ownership and fast execution.
- Other info: Work in a small team with direct access to decision-makers and minimal bureaucracy.
- Why this job: Make a tangible impact by building foundational AI infrastructure that powers multiple products.
- Qualifications: Experience in production AI systems, strong backend engineering skills, and a hands-on approach.
The predicted salary is between 80000 - 100000 £ per year.
LEC AI is the intelligence systems division inside London Export Corporation, a London-headquartered group operating across technology, robotics, logistics, consumer products, and international trade. We are building operational intelligence systems used across real businesses — systems that retain context, retrieve institutional knowledge, coordinate workflows, interact with tools, and improve over time through continuous usage and feedback. This is not a research lab and it is not an “AI wrapper” company. We build production systems operating inside live commercial environments with real users, real operational constraints, and real-world consequences. Our focus is building durable AI infrastructure:
- persistent memory systems
- retrieval and context pipelines
- agent orchestration frameworks
- tooling and execution layers
- evaluation and feedback systems
- operational intelligence infrastructure
The goal is to build systems that become increasingly useful, reliable, and operationally aware over time.
We are hiring a Head of AI Systems Engineering to help build and scale the intelligence infrastructure powering the group. This is a deeply hands-on engineering role focused on designing, building, and operating production AI systems. You will work closely with leadership and the existing AI architecture team to build:
- persistent memory systems
- retrieval and context management infrastructure
- agent orchestration and execution frameworks
- evaluation and improvement loops
- operational tooling systems
- integrations and runtime infrastructure
- scalable foundations for future AI-native products
You will be building systems used across:
- operational AI platforms
- commerce and marketplace systems
- logistics and optimisation tooling
- internal operational workflows
- customer-facing SaaS products
- robotics and telemetry environments
We are looking for someone who enjoys building difficult systems quickly and making them reliable in the real world.
What You Will Do
Build Core Intelligence Systems:
- Design and implement persistent memory infrastructure
- Build retrieval and context management systems
- Develop agent orchestration and execution frameworks
- Create tooling and integration infrastructure
- Improve runtime reliability and operational performance
- Build evaluation and feedback loops for continuous system improvement
Ship Production Infrastructure:
- Write and operate production-grade backend systems
- Improve observability, monitoring, and debugging workflows
- Optimise latency, reliability, and infrastructure efficiency
- Help scale systems across multiple products and business environments
- Build reusable infrastructure rather than isolated point solutions
Work Across Multiple Product Surfaces:
You will help build infrastructure powering:
- operational AI systems
- online sales and marketplace products
- logistics and routing systems
- internal workflow automation
- customer-facing SaaS platforms
- future AI-native products across the group
Who You Are
You have built and operated production AI systems under real-world conditions. Not demos. Not prototypes. Not chains of API calls presented as products. You have experience dealing with:
- unreliable outputs
- orchestration failures
- retrieval quality issues
- context and memory scaling
- tool execution edge cases
- latency and infrastructure constraints
- operational reliability
- systems used daily by real users
You think in systems. You understand that the difficult part of AI is not calling models - it is building reliable infrastructure around memory, orchestration, context, tooling, and execution. You are highly technical and deeply hands-on. You still enjoy writing code and building systems directly. Strong backend engineering fundamentals are essential. Python is expected. Experience with technologies such as:
- Postgres / pgvector
- Redis
- Docker
- Kubernetes
- Neo4j or graph databases
- async systems
- event-driven architectures
- model serving infrastructure is highly valuable.
You move quickly, take ownership, and care about building systems properly. You are comfortable operating with high autonomy and high expectations. We care far more about systems you have built than credentials.
Strong Signals
- Built production agent or orchestration systems
- Designed memory or retrieval infrastructure
- Created evaluation frameworks for AI systems
- Bult platforms used across multiple products or teams
- Experience with tool-calling or integration frameworks
- Open-source infrastructure contributions
- Experience in operational, logistics, robotics, or optimisation environments
- Strong builder mentality and founder-level ownership
- Comfortable in fast-moving environments with minimal bureaucracy
Why This Role Is Different
Real Operating Environments:
The systems you build will operate inside active businesses with live workflows, operational dependencies, and commercial impact.
Foundational Systems Work:
You are not joining to build isolated features. You will help build the intelligence infrastructure underneath multiple products, workflows, and businesses.
High Ownership:
Small team. Fast execution. Direct access to decision-makers. Good ideas move into production quickly.
Serious Technical Problems:
We are interested in durable systems:
- memory
- context
- orchestration
- retrieval
- operational intelligence
- evaluation
- scalable infrastructure
This role suits someone who enjoys complexity, ownership, and building systems that matter.
Location: This role is in London office-based.
How to Apply: Apply on LinkedIn and email your portfolio to talent@lecai.ai with the subject line: Head of AI Systems Engineering. Show us:
- systems you have built
- infrastructure you have operated
- production deployments
- architecture decisions
- technical writing
- GitHub
- real-world engineering work
Head of AI Systems Engineering employer: London Export Corporation
Contact Detail:
London Export Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of AI Systems Engineering
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights the systems you've built and the challenges you've tackled. This is your chance to demonstrate your hands-on experience and technical prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by diving deep into the company’s projects and technologies. Familiarise yourself with their operational AI systems and think about how your experience aligns with their needs. This will help you stand out as a candidate who truly gets what they’re about.
✨Tip Number 4
Don’t just apply anywhere; focus on companies that excite you, like LEC AI! Use our website to submit your application and make sure to tailor your approach to show how you can contribute to building robust AI infrastructure.
We think you need these skills to ace Head of AI Systems Engineering
Some tips for your application 🫡
Show Us Your Work: When applying, make sure to showcase the systems you've built and the infrastructure you've operated. We want to see real-world examples of your engineering prowess, so don’t hold back!
Tailor Your Portfolio: Customise your portfolio to highlight projects that align with our focus on operational intelligence systems. This will help us see how your experience fits into what we’re building at LEC AI.
Be Clear and Concise: In your application, clarity is key! Use straightforward language to explain your technical decisions and the impact of your work. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss any important updates from us!
How to prepare for a job interview at London Export Corporation
✨Know Your Systems Inside Out
Before the interview, make sure you can discuss in detail the production AI systems you've built. Be ready to explain the challenges you faced, how you overcame them, and the impact your systems had on real-world operations.
✨Showcase Your Technical Skills
Prepare to demonstrate your backend engineering fundamentals, especially in Python. Brush up on technologies like Postgres, Docker, and Kubernetes, as you might be asked to solve technical problems or discuss your experience with these tools.
✨Understand the Business Context
LEC AI is all about building operational intelligence systems. Familiarise yourself with their focus areas, such as memory systems and orchestration frameworks, so you can align your answers with their business goals during the interview.
✨Emphasise Your Ownership Mentality
This role requires a strong builder mentality. Be prepared to share examples of how you've taken ownership of projects, moved ideas into production quickly, and navigated fast-moving environments. Highlight your ability to work autonomously while still delivering results.