AI Engineering Lead

2 weeks ago


London, United Kingdom Janus Henderson Investors Full time

Our Mission at Janus Henderson is to help clients define and achieve superior financial outcomes through differentiated insights, disciplined investments, and world-class service. Our Values are key to driving our success, and are at the heart of everything we do:

Clients Come First - Always | Execution Supersedes Intention | Together We Win Diversity Improves Results | Truth Builds Trust

As the Core AI Technology Engineering Lead, you will orchestrate the creation and implementation of foundational AI technologies. This role demands a blend of strategic vision, technical depth, and leadership to steer AI projects from ideation to deployment. Collaborating with diverse teams, you will ensure our AI solutions are robust, scalable, and strategically aligned, driving business transformation and excellence.

Stakeholder Management: Engage with internal and external stakeholders to align expectations and ensure transparent communication regarding product and project planning, as well as capacity commitment.
Cross-functional Collaboration: Work closely with other technology teams and business units to integrate AI technologies seamlessly, fostering a culture of collaboration.
Policy and Standards Development: Design and implement guardrails, policies, standards, and best practices for AI development, ensuring ethical use and consistency.
Encourage a culture of continuous learning and innovation around AI technology and engineering principles within the team.
Project & Product Management: Ensure that the delivery team has a clear understanding of committed deliverables and execution timelines. Actively manage and escalate risks and issues as they arise.
Hands-on Leadership: Participate directly in technical execution, including code reviews, to maintain high standards of quality and performance.

Guide and mentor junior engineers, fostering their professional growth and development in AI engineering.
Ensure Agile and Project Management governance standards, best practices and required reviews are met.
Computer Science, Engineering, Mathematics, or related field of education.
Expertise in AI and machine learning technologies with proficiency in Microsoft Azure offerings such as OpenAI.
Strong programming skills in Python, R, C#, or similar, with experience in cloud computing platforms (AWS, Azure, Google Cloud).
Strong problem-solving skills, with an emphasis on consensus building and collaboration.
Commitment to ethical AI development, with a track record of implementing effective policies and standards.


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