24 hours ago
Toluca, MexicoSenior
Responsibilities
- Create and maintain solution designs for products, features, and backlog stories throughout the agile delivery lifecycle.
- Translate business and technology requirements into scalable, resilient, secure, and cost-effective solutions.
- Provide technical leadership within delivery pods and guide engineering, QA, DevOps, data, and security colleagues.
- Evaluate and incorporate AI and GenAI capabilities, including assistants, semantic search, classification, information extraction, and intelligent automation.
- Apply AI architecture patterns such as RAG, tool or function calling, orchestration, guardrails, caching, and human-in-the-loop controls.
- Identify and communicate architectural risks, technical debt, and AI-related security, privacy, bias, explainability, compliance, and cost risks.
- Collaborate with Platform and Portfolio Architects on architectural strategy, roadmaps, reusable patterns, and AI guardrails.
- Complete architectural governance, control framework, compliance, AI risk assessment, and model governance deliverables where applicable.
- Embed AI testing, evaluation, monitoring, fallback arrangements, documentation, and responsible-use practices into the software development lifecycle.
Requirements
- Strong solution architecture capability and experience translating business requirements into practical technology designs.
- Practical knowledge of AI/ML and GenAI fundamentals, including prompting, embeddings, RAG, agents, fine-tuning, and prompt engineering.
- Understanding of AI architecture patterns, orchestration, guardrails, continuous evaluation, and human-in-the-loop processes.
- Familiarity with model APIs and frameworks such as Azure OpenAI, OpenAI API, Hugging Face, LangChain, and LlamaIndex or equivalent technologies.
- Knowledge of vector search and retrieval technologies, including Azure AI Search, Elasticsearch, OpenSearch, Pinecone, or Weaviate.
- Understanding of MLOps and LLMOps practices, including model and dataset versioning, model registries, prompt management, and experimentation tracking.
- Ability to define and assess AI quality measures such as accuracy, groundedness, toxicity, hallucination, latency, and cost.
- Knowledge of AI security and privacy controls, including prompt-injection protection, data-loss prevention, PII handling, access control, redaction, and content filtering.
- Experience applying security, privacy, responsible AI, data minimisation, retention, traceability, and compliance principles to technology solutions.
- Strong collaboration, communication, and technical leadership skills in an agile, multidisciplinary environment.
Benefits
- Flexible working and opportunities for continuous professional development and career growth.
- Inclusive and diverse workplace with equal opportunity employment practices.
Tech Stack
Elasticsearch
Categories
About HSBC
HSBC is a global bank that provides retail, commercial and investment banking, payments, and wealth management to individuals, SMEs, and multinationals. It earns fees, interest income, and trading revenues through branches and digital platforms across major markets. Headquartered in London, it serves over 40 million customers in 58 countries and is listed in London, Hong Kong, New York, and Bermuda.