oracle
AI Platform Engineering Lead
Schroders
London, GBR
Full-time
Lead
Onsite
Discovered 4 days ago
Full Job Posting
What you'll do
- Own the technical delivery of the Agentic AI Platform from planning through build, release, operation and continuous improvement.
- Lead, motivate and develop a team of highly skilled platform, cloud and AI engineers, creating clear accountability and a strong culture of engineering excellence.
- Set and communicate the technical vision, engineering strategy, architecture principles and delivery roadmap for the platform.
- Translate business objectives and stakeholder requirements into prioritised platform capabilities, user journeys, technical specifications and delivery plans.
- Design and deliver a secure, scalable, self-service platform using AWS Bedrock AgentCore and supporting AWS services.
- Design platform experiences for professional developers, citizen developers, administrators, delivery teams and control functions, balancing simplicity with appropriate flexibility.
- Build guardrails into the platform covering identity, delegated authority, data access, tool use, model access, approvals, auditability and policy enforcement.
- Establish engineering standards for agent orchestration, memory and context, tool integration, human-in-the-loop controls, evaluation, observability and operational support.
- Ensure security, compliance, resilience, cost management and operational readiness are designed into the platform rather than added later.
- Own the platform as a product, using adoption, reliability, support demand, user feedback, delivery performance and cost information to guide improvement.
- Drive a low-overhead operating model through automation, self-service, clear ownership, effective monitoring and reduction of manual operational toil.
- Work with senior stakeholders to explain complex choices clearly, manage expectations, surface risks early and secure alignment on priorities and investment.
- Remain hands-on where it matters: reviewing designs, challenging technical decisions, unblocking complex engineering issues and ensuring delivery quality.
- Manage technical debt, dependencies and platform lifecycle decisions deliberately, ensuring the platform remains supportable as usage scales.
- Promote experimentation and learning while maintaining disciplined controls for production use in a regulated environment.
- The knowledge, experience and qualifications you need
- Proven experience leading high-performing engineering teams that build and operate enterprise platforms or developer-facing products.
- Strong hands-on technical leadership capability, including setting direction, making architecture decisions, establishing engineering standards and taking accountability for delivery outcomes.
- Demonstrable experience building internal developer platforms, self-service platforms, cloud platforms or platform products at enterprise scale.
- Strong product mindset, with experience identifying user personas, mapping user journeys, reducing developer cognitive load and improving platform adoption.
- Hands-on experience designing, building or operating production Agentic AI systems, including orchestration, tool use, memory, context management, guardrails, evaluation and human oversight.
- Strong knowledge of AWS AI and cloud services, particularly AWS Bedrock and AgentCore, together with identity, networking, compute, containers, serverless, storage and observability capabilities.
- Understanding of agent and tool interoperability patterns, including Model Context Protocol, reusable agent skills and controlled integration with enterprise systems.
- Experience applying modern software engineering practices to platforms, including APIs, automated testing, code review, CI/CD, Infrastructure as Code and secure software delivery.
- Ability to gather requirements from technical and non-technical stakeholders and convert them into clear technical specifications, architecture decisions and deliverable increments.
- Experience delivering technology in financial services or another regulated environment, with a strong understanding of security, risk, compliance, auditability and operational resilience.
- Experience designing security-by-default and policy-as-code controls covering access, data, tools, models, deployment and runtime behaviour.
- Strong understanding of production AI concerns, including evaluations, model and agent behaviour monitoring, explainability, failure modes, latency, reliability and cost trade-offs.
- Experience establishing observability and operational controls for distributed platforms, including logging, tracing, metrics, alerting, incident response and service ownership.
- Strong communication and influencing skills, with the ability to explain complex technical choices to engineers, business stakeholders, control functions and senior leaders.
- Commercial and operational awareness, including experience balancing platform investment, cloud consumption, supplier choices, support overhead and sustainable value.
- The knowledge, experience and qualifications that will help
- Experience operating AWS Landing Zone capabilities, including AWS Organizations, Control Tower and enterprise account governance.
- Experience with Python, TypeScript or another modern development language used to build platform services, integrations and agent tooling.
- Experience with Terraform, AWS CDK or CloudFormation and with modular, reviewable Infrastructure as Code.
- Knowledge of retrieval-augmented generation, vector stores, embeddings, knowledge integration and enterprise data access patterns.
- Experience with agent frameworks and AI development tooling such as Strands SDK, Anthropic tooling or comparable technologies.
- Experience building developer portals, service catalogues, skills marketplaces or reusable platform capability catalogues.
- Experience supporting different development archetypes, including professional developers, low-code users and citizen developers.
- Relevant AWS, architecture, security, software engineering or AI qualifications or certifications.
- Evidence of active learning, technical community contribution and the ability to assess emerging technologies pragmatically.
- We Recognise Potential, Whoever You Are
- Our purpose is to deliver excellent investment performance to clients through active management. We believe diverse perspectives and an inclusive culture help us make better decisions and achieve better outcomes for our clients. That's why inclusion is a strategic priority for us, and we are an equal opportunities employer. You are welcome here, regardless of your age, disability, gender identity, religious beliefs, sexual orientation, socio-economic background, or any other protected characteristic.
- We will consider flexible working arrangements for all roles and provide reasonable accommodations to support applicants and employees, including those with neurodiversity, disability, or physical and mental health needs. For more information, please visit our FAQs.
Qualifications
- Experience with Python, TypeScript or another modern development language used to build platform services, integrations and agent tooling.
- Experience with Terraform, AWS CDK or CloudFormation and with modular, reviewable Infrastructure as Code.
- Experience with agent frameworks and AI development tooling such as Strands SDK, Anthropic tooling or comparable technologies.
About Schroders
Asset & Wealth Management5717 employeesFounded 1804
Publicly listed British asset and wealth manager serving institutions, intermediaries and individuals through active public-private market investing.
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