Software Engineer - AI and Innovation

• Develop and deliver AI-enabled features and workflows that solve real business problems, working within agreed product and technical direction.
• Build and maintain production software that integrates with business workflows, data sources, third-party APIs and LLM services such as OpenAI or Anthropic.
• Implement components of agentic AI solutions using Schroders’ standardised agentic infrastructure platform based on AWS Bedrock AgentCore, including tool integrations, user journeys, guardrails and evaluation approaches.
• Work directly with internal customers and colleagues across product, engineering and business teams to clarify use cases, deliver useful increments, and iterate quickly based on feedback.
• Apply quality and security practices, including automated testing, peer review, secure coding and shift-left testing.
• Support the evaluation of AI system behaviour in real use, clearly communicating limitations, risks, quality and user impact.
• Use AI-assisted coding tools responsibly to improve speed, quality and learning, while maintaining clear ownership of code quality.
• Engage in continuous improvement through code reviews, automated testing, documentation, evaluation design and metrics-driven iteration.

We’re looking for an Applied AI Software Engineer to help build and improve AI-enabled products used across the organisation. This is a fast-paced delivery role, ideal for engineers who enjoy working close to business problems, rapid iteration, good engineering practice, and applied AI solutions that deliver real business value. As a member of the team, you’ll contribute to the delivery of Agentic AI systems in applied business contexts. You’ll work directly with internal customers, product owners, business teams and other engineers to turn use cases into safe, reliable and useful software. You should be proficient in Python and modern engineering practices, comfortable contributing across backend and frontend environments, and interested in using AI-assisted development methods responsibly. Strong collaboration, testing discipline, willingness to learn, and a product mindset are essential. If you’re excited by the challenge of building useful AI-enabled software and learning how agentic systems work in production, we’d love to hear from you., * Strong software engineering background, with Python-first development experience.

• Experience building, testing and maintaining production software, APIs, integrations or user-facing features.
• Good understanding of automated testing, code review, CI/CD, debugging and secure coding practices.
• Experience integrating with third-party APIs, business systems or LLM APIs.
• Comfort working in agile teams, breaking work into deliverable increments, and communicating progress clearly.
• Practical understanding of how to test AI outputs, apply responsible AI controls, and explain model limitations and risks before production use.

The knowledge, experience and qualifications that will help

• Experience building applied AI products or features that integrate with LLM API services such as OpenAI or Anthropic.
• Experience using Agentic AI Coding tools to enhance the software delivery process while maintaining high levels of understanding of the resulting code. Using skills, tools and prompting to ensure quality output of those tools.
• Hands-on exposure to enterprise-grade agentic or tool-using AI systems, including orchestration, tool permissions, guardrails, evaluation, human oversight and operational monitoring.
• Experience designing or using evaluations to measure model quality, task completion, safety, regressions and behaviour in multi agent workflows.
• Familiarity with RAG workflows, enterprise data access patterns, vector stores, embedding design, and latency/cost trade-offs.
• Experience working with business stakeholders to shape requirements, test prototypes and turn feedback into working software.
• Experience working with enterprise controls such as identity, access management, auditability, data classification or approval workflows in software delivery.
• Knowledge of agent interoperability and integration standards such as A2A or MCP, particularly where agents need to interact safely with enterprise tools and systems.
• Active contributor to engineering communities, continuous learning, and knowledge sharing.

What you’ll be like

• A curious technologist who stays up-to-date with AI and software trends.
• Open to feedback, willing to ask questions, and keen to learn from more experienced engineers.
• Someone who values quality, security, and solid engineering practices.
• Collaborative communicator, comfortable working with diverse teams across locations and time zones.
• Resilient and positive, able to manage pressure with professionalism.
• Self-motivated, analytical, and solution-oriented with a growth mindset.
• Demonstrates integrity, fairness, and respect for all colleagues.

Schroders is a global investment manager which provides active asset management, wealth management and investment solutions. We aim to provide excellent investment performance to clients through active management. We serve a diverse client base that includes pension schemes, insurance companies, sovereign wealth funds, endowments, foundations, high net worth individuals, family offices, as well as end clients through partnerships with distributors, financial advisers, and online platforms.

Established in 1804, we have around 5,500 people across 36 global locations. Schroders’ success can be attributed to its diversified business model, spanning different asset classes, client types and geographies.

The team

The AI and Innovation team is part of the Global Technology division, operating as a centre of excellence for applied AI and agentic systems. We deliver AI-enabled products and internal tools across multiple areas of the business, helping teams explore, shape and deliver practical AI use cases safely, reliably and efficiently. We work across the full lifecycle from discovery and experimentation through to production use.