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Paid six-month programme for UK service leavers and elite athletes to build professional skills and learn about asset management and financial services. Participants may work across Legal and Compliance, Aladdin Engineering, Client Services and Solutions, Aladdin Client Business, or Internal Audit. Applicants must meet military or professional athlete eligibility criteria and be legally authorized to work in Edinburgh. The programme starts in February 2027 and uses a predominantly office-based hybrid model.

Lead sourcing, evaluation, and management of private credit investments. Conduct due diligence, structure bespoke lending solutions, monitor portfolio performance, and support analytics and reporting for liquid credit portfolios. Role is New York–based with hybrid in-office requirements and is eligible for discretionary bonus and standard benefits.

Provide technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive modeling, and optimization. Design scalable AI platforms, APIs, services, data pipelines, and infrastructure; establish evaluation, testing, observability, security, and governance standards; optimize system performance, reliability, and cost; and partner with multidisciplinary teams to deploy and operate solutions. Mentor engineers and influence technical strategy across the organization.

Supports APAC infrastructure credit investments through financial modeling, cash flow and capital structure analysis, due diligence, deal assessment and execution, investment committee materials, market research, portfolio monitoring, presentations, and fundraising support. The role covers investment-grade and non-investment-grade transactions across energy, transportation, digital, and water and waste infrastructure sectors in developed and emerging Asia-Pacific markets.

Build and lead scalable, production-grade data platforms, pipelines, workflows, and analytics infrastructure for private markets data products. Translate business needs into technical architectures, own solutions through deployment and support, enable AI/ML production use cases, and establish standards for testing, governance, observability, security, and cloud-native development. Partner with engineering, data science, product, and senior stakeholders to deliver reliable, high-impact solutions.

Build and operate enterprise AI platform services, APIs, SDKs, agent runtimes, retrieval systems, evaluation frameworks, observability, guardrails, and governance controls. Lead architecture for scalable, secure, reliable cloud-native services; write production Python code; establish testing, CI/CD, and operational practices; and drive complex technical initiatives. Mentor engineers, shape platform roadmaps, and potentially assume broader people leadership as the team grows.

Lead product marketing for Aladdin Trading’s order and execution management platform. Responsibilities include positioning, technical storytelling, market and competitive insights, value proposition development, go-to-market strategy, product launches, adoption programs, sales enablement, client engagement, and thought leadership. The role partners with product, engineering, design, sales, and ecosystem teams to drive client usage and commercial impact.

Leads flagship AI Labs initiatives from scoping and research through production deployment. Designs and evaluates AI agents and agentic workflows, guides production-grade architecture, establishes quality and safety measurement, and partners with business and engineering stakeholders. Manages and mentors 3–6 AI scientists while communicating technical outcomes to senior leaders and broader audiences.

Provide technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive modeling, and optimization. Design scalable AI platforms, APIs, infrastructure, data pipelines, and observability frameworks. Lead architecture through deployment and continuous improvement while optimizing performance, reliability, security, and cost. Partner with multidisciplinary teams, establish engineering standards, mentor engineers, and translate emerging AI capabilities into measurable business outcomes.

Provides technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive models, and optimization. Establishes architecture, engineering standards, evaluation and observability practices, and reusable AI platforms. Partners across business, engineering, data, risk, and control teams to deploy and operate scalable systems while optimizing performance, reliability, security, and cost. Mentors engineers and influences technical strategy.