Oxford Dynamics hires an Applied Artificial Intelligence Engineer for its London team, with full-time employment and permanent or contract terms considered. The hybrid role develops multi-agent AI software, integrates large language models and vision-language models, and deploys production pipelines across cloud, on-premises, and air-gapped environments. Flexible working hours accompany the London-based arrangement, and Oxford Dynamics has multiple positions available.
An engineer in this position works with engineers, product leads, and customers on evaluation, integration, and secure delivery. Oxford Dynamics requires commercial production experience with agentic AI, strong Python, and practical experience with LLM frameworks such as LangGraph, LangChain, or Haystack. Docker, Git, cloud platforms, and production AI/ML deployment form part of the technical baseline. Active SC or DV clearance is highly desirable for work involving regulated or sensitive environments.
Role: Applied Artificial Intelligence Engineer
Employer: Oxford Dynamics
Location: London, England, United Kingdom
Employment: Full-time, with permanent or contract terms considered
Work arrangement: Hybrid with flexible working hours
Multi-Agent AI Systems
This AI job covers software in which multiple AI agents handle connected parts of a larger workflow. One agent can interpret a task, another can retrieve or transform information, and another can assess an output before the application returns a result. The engineering challenge is to define the boundaries between those steps so that the system remains testable, observable, and controlled.
The role's AI engineering work also covers language models and vision-language models, which process text together with images or other visual material. Engineers evaluate model behaviour, monitor performance, and support system integration with customer environments. This work connects experimental model capabilities with software that has to operate consistently after deployment.
Cloud, On-Premises, And Air-Gapped Delivery
Oxford Dynamics deploys AI applications in cloud environments, on-premises infrastructure, and air-gapped systems. Cloud delivery can use managed services and elastic computing, while an on-premises installation keeps data and processing within an organisation's own environment. An air-gapped deployment removes ordinary network access, so software packages, model files, update procedures, and monitoring controls need a different operating plan.
Secure delivery requires more than selecting a model. The engineer works with containerised services, source control, cloud infrastructure, access permissions, logging, and release checks. Docker, Git, and cloud platform experience support the day-to-day engineering work, while secure-by-design knowledge becomes more important when systems operate in regulated or sensitive settings.
Cloud deployment with platforms such as AWS
- Container work with Docker and related delivery tooling
- Production monitoring for model behaviour and system performance
- Secure deployment for on-premises and air-gapped environments
Python, Frameworks, And Production Standards
The technical baseline combines production software practices with model knowledge. Python is central to the position, and the technical brief names LangGraph, LangChain, or Haystack for LLM and agent development. Production AI/ML deployment experience, Docker, Git, and cloud platforms establish the working baseline.
Strong candidates bring experience with agentic systems rather than only classroom or prototype work. Multimodal systems, Kubernetes, MLOps, observability, model orchestration, MCPs, secure-by-design practices, regulated environments, and open-source AI or machine-learning work are preferred areas. Python, SQL, and JavaScript all belong to the technical language set described in the AI engineer career profile.
Oxford Dynamics And Its Applied AI Work
Oxford Dynamics was founded in 2020 and develops enterprise AI solutions for international defence and security organisations. Its AVIS AI framework combines text, imagery, telemetry, and sensor feeds, while STRIDER is an autonomous robotic platform for hazardous environments. These products place software engineering alongside sensor integration, operational constraints, and secure system design.
Oxford Dynamics is an AI provider working across language models, agent frameworks, and AI-powered software. Its London-based AI work connects customer requirements with systems that operate in demanding environments. The UK public sector also runs public AI projects in London, Bristol, and Manchester that prototype ideas with real users and apply AI to public services.
London Working And Employment Terms
Oxford Dynamics contributes 4% to the NEST pension scheme for this role. Private healthcare is included in the employment package, and the company lists 29 days of holiday plus public holidays.
The position combines those employment terms with work on secure AI systems, customer integration, and production delivery. The London team therefore covers software development alongside deployment constraints that can change between cloud, on-premises, and air-gapped environments.
Degree Routes And Career Progression
Oxford Dynamics prefers a bachelor's degree in computer science, artificial intelligence, data science, or a related subject. Commercial experience remains central to the technical brief, with production agentic AI, LLM deployment, and secure software delivery carrying more weight than a single academic specialism.
UK AI engineering careers can progress into senior technical roles, team or project responsibility, consultancy, or self-employment. Related routes include software development, data science, solutions architecture, and robotics engineering, all of which connect with the systems and deployment work covered by this position.
Technical leadership in the role reaches beyond implementation. The engineer sets technical patterns for junior engineers, helps maintain engineering standards, and supports practical AI adoption with customers. Those duties place reusable engineering decisions alongside day-to-day development.
The position also includes opportunities to develop intellectual property, contribute to AI methodology and research, gain multi-industry expertise, and build technical thought leadership. Experience with secure deployment, multimodal models, and agent frameworks gives the engineer a broad operating brief inside Oxford Dynamics.
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