Lead a multidisciplinary engineering team to deliver AI‑forward, production‑ready solutions for global customers.
Compensation
Software Engineering M5 - The typical base pay range for this role across United Kingdom is £ 93,500.00 - £ 161,800.00 per year.
Responsibilities
Lead a multidisciplinary engineering team, owning a portfolio of work to maximize customer and Microsoft value through strong portfolio and delivery leadership.
Provide clear coaching, career development, and performance support for engineers across software engineering, technical program management, and data science, fostering growth in a multidisciplinary environment.
Serve as a player‑coach by taking on selected engagements, modeling engineering fundamentals, customer‑obsessed execution, and inclusive, cross‑discipline collaboration.
Partner with leadership and discipline managers to ensure healthy team rhythms and strong operational excellence across engagements.
Contribute to a culture of continuous learning by elevating engineering practices, sharing reusable patterns and accelerators, and strengthening our multidisciplinary operating model.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality.
Responsibilities
Perform independently and become an SME
Participate in team discussions
Provide solutions to work related problems
Collaborate with stakeholders to understand project requirements and translate them into technical solutions
Continuously monitor and optimize AI models and systems to maintain high performance and reliability
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence technologies and cloud-based AI services. The role requires managing end-to-end application pipelines, ensuring solutions are production-ready and scalable.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with stakeholders to understand project requirements and translate them into technical solutions.
Continuously monitor and optimize AI models and systems to maintain high performance and reliability.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with stakeholders to understand project requirements and translate them into technical solutions.
Continuously monitor and optimize AI models and systems to maintain high performance and reliability.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with stakeholders to understand project requirements and translate them into technical solutions.
Continuously monitor and optimize AI models and systems to maintain high performance and reliability.
