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Capital Group

Asset management with long-term portfolios

Software Development Engineer 2

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • Substantial experience leading complex software, platform, cloud, data, or artificial intelligence engineering initiatives, including helping build or scale a capability from an early stage.
  • Demonstrable hands-on engineering depth, including the ability to contribute production code, lead technical design, and constructively challenge architecture.
  • Hands-on experience designing, building, and shipping software and artificial intelligence or machine-learning solutions for real business problems.
  • Practical knowledge of prompt engineering, retrieval architectures, agent development, and evaluation methods for generative artificial intelligence systems.
  • Strong software engineering fundamentals, including application programming interfaces, system design, distributed-systems concepts, cloud-native development, testing, continuous integration and continuous delivery, and production operations.
  • Strong front-end and user-interface development experience, including building responsive, accessible, user-centred interfaces using modern web frameworks and design-system patterns.
  • Experience integrating applications with enterprise data platforms and working across structured and unstructured data, metadata, semantic or context layers, and data-quality controls.
  • A track record of influencing senior technology and business stakeholders and translating effectively between business outcomes and technical decisions.
  • Systems thinking and high agency, with the judgement to navigate ambiguity and make pragmatic trade-offs between scope, speed, risk, cost, and quality.
  • Excellent written and spoken communication, with the ability to explain complex topics clearly to technical and non-technical audiences.
  • A bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • The right to work in the UK, the ability to work from London on a hybrid basis, and openness to travel and collaborate across time zones, particularly with US teams.
  • Operate with urgency, ownership, humility, and strong collaboration.
  • Move confidently between strategic context, architectural decisions, and detailed engineering implementation.
  • Maintain high standards for code quality, testing, clarity, security, and reliability, applying judgement about which standards matter most in each context.
  • Challenge constructively, propose better alternatives, and protect quality and team capacity when it counts.
  • Stay current as models, tooling, and engineering practices evolve, and help others learn and adapt.
  • Be motivated by meaningful impact, strong engineering outcomes, and the growth of those around you.

Responsibilities

  • Partner directly with business and product leaders to understand workflows, identify high-value opportunities, and translate ambiguous needs into clear outcomes, acceptance criteria, and technical specifications.
  • Design, build, and operate modern full stack applications, application programming interfaces, data workflows, and user-facing capabilities supporting Enterprise Data Office Content Delivery priorities.
  • Develop intuitive, accessible, and maintainable front-end and user-interface experiences that make Enterprise Data Office applications easier to use, support, and extend.
  • Help establish strong full stack engineering practices across the team, setting a high bar for technical quality, collaboration, inclusion, and continuous learning.
  • Use artificial intelligence-enabled tools and practices to improve discovery, engineering productivity, testing, documentation, data quality, and operational support where appropriate and well controlled.
  • Implement end-to-end retrieval-augmented generation solutions, including parsing, ingestion, chunking, metadata, embeddings, vector storage, retrieval, reranking, context assembly, and prompt management.
  • Apply sound system-design and distributed-systems judgement across structured and unstructured data, with particular attention to data quality, lineage, cataloguing, and access controls.
  • Deliver solutions end to end, from partnering on discovery and architecture through implementation, controlled rollout, adoption, and ongoing operations.
  • Practise evaluation-driven development by defining acceptance criteria early and building automated evaluation harnesses that measure correctness, groundedness, hallucination, safety, latency, and task success.
  • Implement observability, monitoring, cost attribution, audit trails, and service-level measures so teams can detect degradation, diagnose failures, and prevent regressions.
  • Use engineering metrics and measurable value outcomes to guide technical investment, improve delivery, and demonstrate the impact of artificial intelligence capabilities.
  • Lead solution reviews and technical decision-making across initiatives, balancing speed, quality, risk, maintainability, and business value.
  • Contribute code and hands-on problem solving where it creates the greatest leverage, particularly for complex designs, reusable components, and production-critical issues.
  • Coach and mentor engineers across artificial intelligence, software, data, and platform disciplines, helping them build practical skills and sound engineering judgement.
  • Codify successful approaches into reusable services, libraries, patterns, reference architectures, and playbooks that accelerate the wider organisation.
  • Build strong partnerships across global teams and time zones, influencing outcomes.

Desired Qualifications

  • Experience in financial services or another highly regulated enterprise environment.
  • Experience with public cloud and modern data or artificial intelligence platforms, including technologies such as AWS, Azure AI, or Databricks.
  • Experience designing and delivering full stack applications across front-end, application programming interface, service, and data layers, with a strong understanding of how user experience, business logic, and data quality fit together.
  • Strong hands-on experience with modern front-end and user-interface development, including component-based frameworks, responsive design, accessibility, usability, and integration with enterprise design standards.
  • Experience building reliable backend services, application programming interfaces, and integrations, including authentication, authorisation, observability, testing, continuous integration and continuous delivery, and secure production support.
  • Experience enhancing existing applications with artificial intelligence-enabled capabilities, automation, or intelligent user experiences, while applying sound engineering judgement, controls, and maintainability practices.
  • Experience mentoring senior engineers, setting technical standards, and influencing engineering practice across organisational boundaries.

About the Company

Capital Group

Asset management with long-term portfolios

Capital Group is a private investment firm managing equity and fixed-income assets for millions of investors. It builds long-term, high-conviction portfolios using rigorous research and the American Funds lineup to pursue steady, durable results rather than short-term trades. It differentiates itself through strong personal accountability, a globally distributed team, and a research-driven investment process. Its goal is to improve people’s lives through successful investing.

Company size
5,001-10,000
Company stage
Not listed
Total funding
$65.4B
Headquarters
Dongcheng District, China
Founded
Not listed

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