A vacancy has arisen for a Sqn Ldr (Any) to serve as SO2 Artificial Intelligence & Machine Learning at HWY on Full Time Reserve Service (Limited Commitment) Terms and Conditions of Service (TCoS) with an initial proposed start date of 08 September 2026.
Artificial Intelligence (AI) and Machine Learning (ML) are central to delivering operational advantage and decision superiority in a contested data-driven battlespace. This post will lead the coherence prioritisation and assured transition of Airs AI & ML experimentation working at pace whilst remaining aligned to Defence-level governance the Defence AI Centre (DAIC) and the digital ecosystem that underpins integration and scale. As Airs focal point for AI & ML experimentation and exploitation with particular responsibility for cohering ongoing projects ensuring they are positioned to successfully transition into enduring capabilities appropriately owned across Defence or by RAF Digital.
The posts responsibilities are:
Lead and cohere Airs AI&ML experimentation portfolio setting direction and priorities aligned to operational outcomes.
Provide oversight of AI&ML activity ensuring projects address clear user needs and are positioned for successful transition into enduring capability without duplicating project-level delivery.
Align Air activity with the Defence AI Centre (DAIC) leveraging Defence-wide support expertise and delivery routes.
Advocate for and exploit emerging AI&ML technologies working with National Armaments Digital and Data and RAF Digital to enable integration and scale.
Enable the transition of AI&ML prototypes into operational capability ensuring appropriate ownership assurance and sustainment.
Shape Airs AI&ML research priorities with Dstl linking operational challenges to future capability development.
Engage with industry and academic partners to track developments and strengthen Airs position within the wider AI ecosystem.
Provide clear reporting and advice to governance bodies supporting prioritisation risk management and informed decision-making.
A vacancy has arisen for a Sqn Ldr (Any) to serve as SO2 Artificial Intelligence & Machine Learning at HWY on Full Time Reserve Service (Limited Commitment) Terms and Conditions of Service (TCoS) with an initial proposed start date of 08 September 2026. Artificial Intelligence (AI) and Machine Learn...
A vacancy has arisen for a Sqn Ldr (Any) to serve as SO2 Artificial Intelligence & Machine Learning at HWY on Full Time Reserve Service (Limited Commitment) Terms and Conditions of Service (TCoS) with an initial proposed start date of 08 September 2026.
Artificial Intelligence (AI) and Machine Learning (ML) are central to delivering operational advantage and decision superiority in a contested data-driven battlespace. This post will lead the coherence prioritisation and assured transition of Airs AI & ML experimentation working at pace whilst remaining aligned to Defence-level governance the Defence AI Centre (DAIC) and the digital ecosystem that underpins integration and scale. As Airs focal point for AI & ML experimentation and exploitation with particular responsibility for cohering ongoing projects ensuring they are positioned to successfully transition into enduring capabilities appropriately owned across Defence or by RAF Digital.
The posts responsibilities are:
Lead and cohere Airs AI&ML experimentation portfolio setting direction and priorities aligned to operational outcomes.
Provide oversight of AI&ML activity ensuring projects address clear user needs and are positioned for successful transition into enduring capability without duplicating project-level delivery.
Align Air activity with the Defence AI Centre (DAIC) leveraging Defence-wide support expertise and delivery routes.
Advocate for and exploit emerging AI&ML technologies working with National Armaments Digital and Data and RAF Digital to enable integration and scale.
Enable the transition of AI&ML prototypes into operational capability ensuring appropriate ownership assurance and sustainment.
Shape Airs AI&ML research priorities with Dstl linking operational challenges to future capability development.
Engage with industry and academic partners to track developments and strengthen Airs position within the wider AI ecosystem.
Provide clear reporting and advice to governance bodies supporting prioritisation risk management and informed decision-making.