AI Technical Architect

Description

Work collaboratively with different areas of the Bank to design robust architectures capable of meeting functional and non-functional requirements, including technology, security, performance, resilience, scalability, integration and observability.

Assess technical feasibility and design solutions in response to business needs, in close alignment with the Santander CTO team's guidelines, Bank policies, and Group Architecture principles.

Key responsibilities

• Lead the design of end-to-end AI solutions, including ingestion, transformation, storage, serving, consumption, application integration and operationalization components.
• Define architectures for analytical, predictive, generative and intelligent automation use cases.
• Ensure proposed solutions incorporate security by design, privacy by design, resilience by design and operability by design principles.
• Promote architecture patterns, reusable components, reference frameworks and best practices in software, data and AI engineering.
• Contribute to technology modernization strategies, legacy integration and evolution of the Bank's Data and AI platforms.
• Work with cross-functional teams (IT - DEV, CIO, CISO, CTO, Operations and Business).
• Support technology decisions by analysing trade-offs between cost, complexity, risk, time-to-market and future evolution.
• Ensure designs cover deployment across cloud, hybrid and on-prem environments per corporate standards.
• Continuously identify opportunities to improve, simplify and rationalize technical solutions.
• Stay current on emerging trends in Data, AI, GenAI and distributed platforms.

Mandatory requirements

• 5+ years of proven experience in Technical Architecture roles, with AI-specific experience valued.
• Solid experience designing enterprise-scale architectures.
• Cloud and hybrid architectures (Azure, AWS, private cloud - OHE).
• Strong knowledge of AI/ML and GenAI architectures: frameworks, integration patterns, pipeline orchestration, vector stores, RAG, model serving, guardrails and model observability.
• Experience integrating enterprise AI services (e.g. Azure OpenAI).
• Distributed systems patterns: APIs, events, micro-services, async processing.
• Agile delivery experience.
• Legacy system integration / modernization.
• Solid technical knowledge of Python, SQL, Java/Spring, JavaScript and similar.
• Modern engineering practices: CI/CD, IaC, automation, observability, testing, versioning, controlled deployment.
• Excellent English communication skills. Spanish is a plus.
• Bachelor's or Master's in Computer Engineering, Computer Science, Electrical Engineering or equivalent.

Valued AI-specialist requirements

• Experience designing enterprise AI platforms.
• MLOps / LLMOps: model lifecycle, environment promotion, evaluation, monitoring, versioning, drift control.
• AI governance: explainability, auditability, observability, risk control, prompt security, filtering, guardrails, hallucination management.
• RAG, embeddings, semantic search, vector databases, LLMs + enterprise knowledge integration.
• Secrets management, environment segregation, technical identity, secure integration with corporate platforms.
• Architecture and security in banking/regulated contexts.
• Tech evolution roadmaps and architecture standards for Data & AI domains.
• Experience with the Noxus platform is a plus.

Soft skills

• Communicate complex technical concepts clearly to technical and non-technical audiences.
• Strong analytical and problem-solving skills.
• High critical thinking, attention to detail and technical rigor.
• Ability to influence and facilitate across teams with different priorities.
• Collaborative, proactive, continuous-improvement mindset.
• Time management and prioritization across competing demands.
• Long-term focus on quality, resilience and sustainability.

Additionally valued

• Prior experience in banking or highly regulated contexts.
• Participation in technology transformation, application modernization or AI platform industrialization initiatives.
• Production and review of technical designs, standards, principles and architecture governance.
• Ability to act as technical reference supporting delivery teams.