AI Solution Engineer

Job Description

hackajob is collaborating with Raytheon to connect them with exceptional professionals for this role.

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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.

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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.

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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.

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Key Responsibilities:

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• \nSupport the development and implementation of AI/ML solutions ensuring alignment with Army training objectives and Omnia architecture principles.\n

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• \nContribute to the design, development, and deployment of AI/ML solutions aligned to Army training objectives and enterprise architecture principles.\n

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• \nDevelop and maintain ML pipelines including data preprocessing, feature engineering, model training, validation, and performance evaluation.\n

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• \nSupport integration of AI capabilities into secure operational environments, ensuring compatibility with DevSecOps pipelines and platform constraints.\n

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• \nMonitor deployed models, analyse performance metrics, and implement tuning or retraining strategies to maintain operational effectiveness.\n

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• \nCollaborate with data engineers and software teams to ensure scalable, maintainable, and secure AI components.\n

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• \nApply ethical AI principles including bias mitigation, data governance, and regulatory compliance in defence contexts.\n

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• \nProduce high-quality technical documentation to support maintainability, auditability, and knowledge transfer.\n

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• \nSupport stakeholder engagement through demonstrations, technical briefings, and translation of complex AI concepts into accessible insights.\n

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• \nEvaluate emerging AI tools and platforms for applicability to Army training use cases.\n

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• \nActively develop technical capability through structured learning and mentorship.\n

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• \nAll other tasks required to deliver the programme.\n

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Who we are looking for:

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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.

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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.

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Essential Skills and Experience:

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• \nStrong Python programming skills for AI/ML development.\n

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• \nHands-on experience with at least one major ML framework (e.g. PyTorch, TensorFlow, scikit-learn).\n

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• \nExperience building and maintaining end-to-end ML pipelines (data ingestion, pre-processing, training, evaluation, deployment) and deployment to production environments.\n

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• \nUnderstanding of feature engineering, model validation, and performance evaluation techniques.\n

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• \nExperience integrating ML components into wider software systems via APIs or microservices.\n

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• \nExperience working with version control (Git) and collaborative engineering practices\n

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• \nExperience contributing to CI/CD pipelines and containerised deployments (e.g. Docker, Kubernetes)\n

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• \nExperience working with cloud or controlled compute environments\n

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• \nAbility to document technical solutions for maintainability, audit, and operational support\n

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• \nUnderstanding of secure coding principles and data protection requirements\n

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• \nAwareness of responsible AI considerations (bias mitigation, explainability, privacy)\n

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• \nAbility to work within regulated or governed environments and frameworks\n

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• \nStrong analytical and problem-solving capability\n

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• \nAbility to communicate technical concepts to non-technical stakeholders\n

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• \nExperience collaborating within cross-functional engineering teams\n

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