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AI Solution Engineer

Raytheon -
Warminster

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Job details

Full-time

Qualifications

TensorFlow
Kubernetes
PyTorch
Software deployment
Git
Microservices
Analysis skills
Docker
Continuous improvement
APIs
AI
Python

Full job description

Date Posted:

2026-05-27

Country:

United Kingdom

Location:

Warminster, Wiltshire

Position Role Type:

Hybrid

About us:
At OMNIA® Training, we’ve brought together some of the UK’s most innovative defence training organisations under one powerful mission: to transform the British Army’s training system and create the best-trained Army in the world.

OMNIA are redefining the British Army’s collective training. To do that, we are looking for the best and brightest minds from across the UK. We are backed by British innovation and powered by world-class experts, like you. OMNIA is at the heart of the UK’s bold Land Industrial Strategy.

The role:
You’ll work in a matrix organisation and report operationally through OMNIA Training and functionally through the OMNIA AI Solutions Lead. Ultimately, you’ll work for the British Army, championing innovation, and helping shape the future of military collective training.

Key Responsibilities:

Support the development and implementation of AI/ML solutions ensuring alignment with Army training objectives and Omnia architecture principles.
Contribute to the design, development, and deployment of AI/ML solutions aligned to Army training objectives and enterprise architecture principles.
Develop and maintain ML pipelines including data preprocessing, feature engineering, model training, validation, and performance evaluation.
Support integration of AI capabilities into secure operational environments, ensuring compatibility with DevSecOps pipelines and platform constraints.
Monitor deployed models, analyse performance metrics, and implement tuning or retraining strategies to maintain operational effectiveness.
Collaborate with data engineers and software teams to ensure scalable, maintainable, and secure AI components.
Apply ethical AI principles including bias mitigation, data governance, and regulatory compliance in defence contexts.
Produce high-quality technical documentation to support maintainability, auditability, and knowledge transfer.
Support stakeholder engagement through demonstrations, technical briefings, and translation of complex AI concepts into accessible insights.
Evaluate emerging AI tools and platforms for applicability to Army training use cases.
Actively develop technical capability through structured learning and mentorship.
All other tasks required to deliver the programme.

Who we are looking for:

You’ll have a mission focus, and the enthusiasm and drive to ‘get things done’. You’ll want to work in collaboration with other defence training organisations, and the British Army. You won’t let bureaucracy get in the way of what needs to be done, you’ll learn lessons and share these lessons across the team. You’ll understand what it means to put the mission first.

The successful candidate will support the development and integration of AI/ML models aligned with Army training goals and OMNIA architecture, assisting with data preparation, model evaluation, and workflow automation. They will collaborate with technical teams, document processes, monitor model performance, and contribute to ethical AI practices. The role also involves learning emerging technologies, supporting stakeholder communications, and working within DevSecOps engineers to ensure smooth deployment and continuous improvement.

Essential Skills and Experience:

Strong Python programming skills for AI/ML development.
Hands-on experience with at least one major ML framework (e.g. PyTorch, TensorFlow, scikit-learn).
Experience building and maintaining end-to-end ML pipelines (data ingestion, pre-processing, training, evaluation, deployment) and deployment to production environments.
Understanding of feature engineering, model validation, and performance evaluation techniques.
Experience integrating ML components into wider software systems via APIs or microservices.
Experience working with version control (Git) and collaborative engineering practices
Experience contributing to CI/CD pipelines and containerised deployments (e.g. Docker, Kubernetes)
Experience working with cloud or controlled compute environments
Ability to document technical solutions for maintainability, audit, and operational support
Understanding of secure coding principles and data protection requirements
Awareness of responsible AI considerations (bias mitigation, explainability, privacy)
Ability to work within regulated or governed environments and frameworks
Strong analytical and problem-solving capability
Ability to communicate technical concepts to non-technical stakeholders
Experience collaborating within cross-functional engineering teams

RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.

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