Head of AI Systems Engineering
LEC AI | London | Full-Time | Office-based
About LEC AI
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.
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The Role
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.
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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
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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.
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Strong Signals
* Built production agent or orchestration systems
* Designed memory or retrieval infrastructure
* Created evaluation frameworks for AI systems
* Built 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
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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.
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Location
This role is in London office-based.
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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