4 days ago
Base Salary
$235k - $285k/yr
Responsibilities
- Take AI ideas from prototypes through hardened, scalable, production-grade systems.
- Design, implement, deploy, and evolve autonomous and tool-using AI systems for internal and customer-facing use.
- Build agent orchestration architectures involving single and multi-agent systems, tool and function calling, Model Context Protocol, agent-to-agent coordination, planning, reasoning, memory, identity, access, and safety controls.
- Assess business problems and select appropriate models, agent patterns, and architectures.
- Track emerging models, agentic frameworks, techniques, and tooling and bring suitable innovations into production.
- Deliver reliable software within the governance, risk, compliance, and audit requirements of a regulated environment.
- Work directly with stakeholders to shape roadmaps and translate business goals into AI capabilities.
- Define standards for AI quality, evaluation, observability, and responsible-AI practices.
- Provide technical direction and architecture leadership across teams.
Requirements
- Proven experience building production AI/LLM applications that internal teams or customers rely on.
- Demonstrated ability to move rapidly from proof of concept to hardened, scalable, maintainable production systems.
- Proven track record delivering production software in a regulated environment, such as financial services, within governance, risk, compliance, and audit controls.
- Hands-on experience building agentic AI systems that reason, plan, call tools, take actions, and support multi-agent and agent-to-agent coordination.
- Experience with Model Context Protocol, tool and data integration, and controls for trustworthy autonomous behavior.
- Understanding of identity and access for AI agents, including delegated user authority, non-human identities, authentication, authorization, and auditability.
- Strong software engineering fundamentals, including reliable, observable, testable, and maintainable systems.
- Strong communication and stakeholder skills, including the ability to move between business discussions and technical design.
- Comfort working with ambiguity, staying close to business and user needs, and shipping iteratively.
- Experience with retrieval-augmented generation, AI evaluation, guardrails, safety controls, prompt and context design, and memory is strongly desirable.
- Experience leading architecture across teams and selecting among models, agent patterns, and architectures is desirable.
- Customer-facing AI experience and exposure to agent-driven or AI-generated user interfaces are nice to have.
Categories
Forward Deployed
About Barclays
Barclays is a UK‑based universal bank that provides retail and commercial banking, credit cards (Barclaycard), wealth management, and investment banking to consumers, businesses, and institutions. Publicly listed in London and New York, it generates revenue from net interest income, fees, and markets activities, and operates across Europe, the Americas, the Middle East, and Asia. Founded in 1690 and headquartered in London, it serves customers through digital channels and a branch network.