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    Core AI Engineering Lead - london, United Kingdom - Janus Henderson Investors

    Janus Henderson Investors
    Janus Henderson Investors london, United Kingdom

    4 days ago

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    Description
    Job Description

    Why work for us?

    A career at Janus Henderson is more than a job, it's about investing in a brighter future together.

    Our Mission at Janus Henderson is to help clients define and achieve superior financial outcomes through differentiated insights, disciplined investments, and world-class service. We will do this by protecting and growing our core business, amplifying our strengths, and diversifying where we have the right.

    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

    If our mission, values, and purpose align with your own, we would love to hear from you

    Overview of the role

    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.

    Duties and responsibilities

    • Strategic Leadership: Develop and execute an AI technology strategy that supports business change initiatives, including a 1 to 3-year roadmap that aligns with company goals.
    • 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.
    • AI Advocacy: Educate and demystify AI technology for non-technical stakeholders, promoting its value and applicability across the organization.
    • Policy and Standards Development: Design and implement guardrails, policies, standards, and best practices for AI development, ensuring ethical use and consistency.
    • Fostering a Learning Culture: 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.

    Coaching & Leadership

    • Keep teams aligned on vision, direction and scope as set by the Program team
    • 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.
    • Cultivate Team Spirit: Champion the development of a team culture that emphasizes collaboration, support, and a shared vision, making every member feel they are part of something bigger than themselves.

    Skills and qualifications

    • 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.
    • Excellent stakeholder management skills, capable of fostering strong relationships with both business and technology stakeholders.
    • Ability to present complex ideas in a clear and engaging manner, facilitating understanding and buy-in from all levels of the organization.
    • Commitment to ethical AI development, with a track record of implementing effective policies and standards.
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