AI Technologist

Essential Qualifications/Experience:

·       University degree in Computer Science, Computer Engineering, Software Engineering, or a closely related field. A PhD in a relevant discipline is preferred

·       10+ years of professional experience in software engineering, AI/ML system development, or related technical disciplines, with demonstrated expertise in the full software development lifecycle

·       Hands-on expertise in AI/ML frameworks and tools, including but not limited to: PyTorch, TensorFlow, scikit-learn, or equivalent. Demonstrable experience implementing and evaluating ML models in production or research environments

·       Strong proficiency in software development using one or more of the following languages and frameworks: Python, Java, C#/.NET, JavaScript/TypeScript. Experience with backend frameworks such as Spring Boot, or equivalent enterprise-grade platforms

·       Experience in the design and development of distributed software architectures, including microservices, RESTful APIs, cloud-native components (AWS, Azure, or equivalent), and containerised deployment using Docker and Kubernetes

·       Experience in research project management, including contribution to research proposals, scientific studies, project planning, and reporting in a technical or academic context

·       Demonstrated ability to design, implement, and evaluate AI/ML software prototypes and demonstrators, including documentation of technical results in reports and specifications

·       Experience working in project teams with international composition, including both military and civilian stakeholders, and adapting to different organisational environments

·       Experience contributing to NIAG (NATO Industrial Advisory Group) studies or equivalent NATO science and technology activities

·       Candidate must have the nationality of one of the NATO nations

Desirable Qualifications/Experience:

·       Experience with NATO C4ISR systems or defence-related software development, including familiarity with relevant standards and mission application architectures (e.g. BMC3I systems, JCHAT, XMPP, Link16, NVG)

·       Experience with AI/ML use cases relevant to the defence domain, such as signal classification, anomaly detection, trajectory prediction, or multi-sensor data fusion

·       Experience with knowledge graph technologies, vector databases, semantic search, and retrieval-augmented generation (RAG) systems, particularly for large-scale data analysis applications

·       Familiarity with responsible AI principles, including model explainability techniques (SHAP, LIME, attention visualisation), fairness metrics, and AI governance frameworks

·       Experience with agile development methodologies and collaborative software development practices (e.g. Git, CI/CD pipelines, code review)

·       Knowledge of NATO responsibilities and organisation, including ACT and ACO

·       Prior working experience in an international environment comprising both military and civilian elements

DUTIES/ROLE:

·       Leading the identification and scoping of AI/ML use cases applicable to (T)BMD fire-control coordination and IAMD operational challenges

·       Reviewing existing NIAG SG300 reports and TBMD simulation data to establish baseline knowledge and identify relevant datasets

·       Designing a baseline data architecture and methodological framework for the responsible use of advanced AI technologies within the BMD domain, informed by NATO’s current AI architecture and near-term plans

·       Conducting feasibility studies on emerging AI/ML computational techniques (such as machine learning, deep learning, reinforcement learning, and large language models) and assessing their potential operational benefit for identified use cases

·       Developing and evaluating AI/ML software prototypes and demonstrators for selected BMD use cases at NATO UNCLASSIFIED level in the NATO Software Factory (NSF). All development to take place in NSF and to use existing LLMs where needed (to make it easier to migrate to NS)

·       Preparing and providing subject matter (BMD AI) briefings, expert reports, and feasibility study documentation related to the project work

·       Developing and documenting a responsible AI framework aligned to the NATO Principles of Responsible AI Use (PRU), as outlined in the NATO AI Strategy, but specifically tailored to the BMD context. This work should follow NATO ambition and align with existing work on the topic as required

·       Planning and delivering subject matter (BMD AI) training and knowledge transfer sessions to the NCIA project team and a wider NCIA community, focusing on the BMD case. NCIA will share currently available AI training material with the contractor team