岗位描述
Partner with cross-functional stakeholders to define, build and implement a Generative AI Agent platform supporting priority banking services from discovery through production rollout. Architect enterprise-grade platform capabilities, including agent orchestration (supervisors/super agents), workflow design, tool/function integration, memory and state management, skill registry/management, and reusable patterns that enable consistent delivery across teams. Drive platform adoption at scale by creating reference implementations, onboarding pathways, developer enablement (APIs/SDKs, templates, documentation), and governance that accelerates safe, repeatable delivery of agent solutions. Own platform performance management: define success metrics and SLOs, implement observability (logs/metrics/traces), run evaluations, and continuously tune reliability, accuracy, latency and cost to optimise outcomes. Oversee end-to-end delivery execution, proactively managing scope, risks, dependencies and milestones; coordinate across teams to remove blockers and ensure timely, high-quality outcomes. Act as a trusted advisor to senior leadership, translating technical options into clear recommendations, trade-offs (value/risk/cost), and delivery plans to support informed decision-making. Stay current on GenAI/agent advancements (including LangChain/LangGraph and emerging alternatives), assess applicability to HSBC use cases, and drive pragmatic upgrades that keep the platform secure, compliant and competitive. Education & English: Bachelor's degree or above in Computer Science/Engineering (or related); strong communication skills including verbal communication in English. Software Engineering: 5+ years' hand on coding practice, strong Python or Java or Golang, with usage of at least one major cloud (AWS/Azure/GCP); ability to deploy and operate services in production (Docker/Kubernetes preferred). GenAI / LLM Delivery: 2+ years building and shipping LLM/GenAI applications; Proven practices with agentic workflows, multi-agents, and tool/function calling, and RAG, search, and vector databases, design & develop agent tooling and integration patterns (e.g., MCP and tool/function calling) SME and deeper experience in at least one area (Performance Monitoring, Agent Governance Control, Agent Identity, Harness, Agent SDK, Agent Policy / Guardrail) Be able to demonstrate a strong vision for the future of agent platforms. Be able to articulate concrete best practices for creating skills, agents, or MCP tooling. Problem-solving & commitment, strong ability to develop creative solutions to complex challenges, working effectively with technical and non-technical stakeholders. Demonstrates an AI-native mindset by applying AI-driven approaches, including coding assistants, to improve productivity, quality, and engineering best practices.