Tech Lead AI Conversational Agents

• Minimum of 5 years of experience in software development and participation in technology projects in production environments, including the design, implementation, integration, maintenance, and evolution of business-oriented solutions.
• Experience leading technology solutions, guiding engineering teams, and using agile methodologies.
• Essential experience and strong knowledge of Python.
• Experience in applied AI, NLP, software engineering, data, or automation in production environments.
• Hands-on experience building and maintaining chatbots/voicebots in production (web/WhatsApp/IVR).
• Experience with LLMs in real-world use cases: prompting, RAG/semantic search, quality evaluation, guardrails, and hallucination mitigation.
• Experience in analytics and monitoring: event instrumentation, logs, dashboards, and metrics
• Experience integrating with MCPs, REST APIs/webhooks, and corporate systems.
• Experience with conversational platforms (at least one): Dialogflow, Azure Bot Framework, Amazon Lex, IBM Watson Assistant, Genesys, LivePerson, Kore.ai, Cognigy (desirable).
• Knowledge of MLOps/LLMOps practices (desirable): versioning, deployments, monitoring, rollback.
• Experience in regulated environments / sensitivity to security and privacy (PII, GDPR) (desirable)

• Degree in Computer Engineering, Telecommunications, Mathematics/Statistics, Data Science, Physics, or similar.
• Master's or postgraduate degree in AI, Data Science, NLP, Software Engineering (desirable).
• Certifications (desirable):
  • Cloud Fundamentals (AWS/Azure/GCP)
  • NLP/Conversational AI (any recognized vendor)
  • Scrum/Agile (PSM/CSM)
  • Responsible AI / Security (desirable)

• Spanish: native or equivalent. (Required)
• English: C1 (technical documentation, meetings with vendors, international coordination). (Preferred)

Your contribution matters and is recognized. You can expect a fair and competitive rewards package that reflects the impact you create and the value you deliver. But we know that rewards go beyond numbers.

• We enable our teams to go further through global opportunities and expansive career paths.

• Flexibility that works. Enjoy hybrid work models, with some days remote and others in person with your team, along with flexible hours.

• Lifelong learning. Access hundreds of courses on our platforms, including exclusive access to our global learning hub: Santander Open Academy (www.santanderopenacademy.com)

• Competitive rewards. Receive a highly competitive salary with performance-based bonuses, keeping you motivated to grow with us.

• Financial benefits. Enjoy preferential banking conditions, special interest rates on loans, life insurance, and more.

• Your health is our priority. Through BeHealthy, our global wellness program, we promote holistic well-being.

• We know that family comes first. That's why we offer childcare support and family programs tailored to every stage of life.

• Always by your side. Access Santander Contigo, our program for employees and their families offering legal, emotional, and administrative advisory services.

• Additional benefits. Gym membership/WellHub, medical centers at some of our facilities, meal allowance, parking, shuttle service from various points in Madrid, as well as exclusive discounts and offers for Santander employees. And that's just the beginning: we'll tell you more when you join!

We are here to keep you motivated, help you reach your goals, and celebrate your progress every step of the way.

Tech Lead AI Conversational AgentsCountry: Spain

Santander Spain is looking for its Data & AI area for a Tech Lead AI Conversational Agents based in Madrid (Edificio Luca de Tena).

We are shaping the way we work through innovation, cutting-edge technology, collaboration, and the freedom to explore new ideas. To succeed in this role, you will be responsible for:

• Technically lead the implementation and evolution of conversational agents (chat/voice) in production following architecture, security, and quality standards.
• Provide guidance to engineers and squads through the definition of design patterns, cookbooks, and engineering best practices.
• Manage technical debt of the products under their scope, providing input to Product Owners and actively influencing its resolution.
• Collaborate closely with architects, acting as a key input for the evolution, productization, and improvement of the technical architecture components.
• Define and oversee standards, rules, reference architectures, and cookbooks to reduce the cognitive load of engineering teams.
• Industrialize the use of AI agents through common harnessing capabilities, ensuring scalability, resilience, observability, and secure operation in Enterprise environments.
• Configure and optimize intents, entities, slots, context, flows, disambiguation, fallback, and handoff to human agents.
• Prepare and maintain conversational datasets: cleaning, labeling, versioning, and quality control.
• Define and execute technical evaluation: intent precision/recall, confusion, coverage, and LLM evaluation (rubrics, human eval, safety checks).
• Integrate the agent with internal systems via MCPs, APIs, or enterprise Knowledge Bases.
• Implement security and compliance controls: PII redaction, access control, logging/auditing, retention, and internal policies.

Our people are our greatest strength. Each individual brings unique perspectives that make us stronger as a team and as an organization. We are empowering teams to go further by valuing who they are and maximizing what they contribute.

The following requirements represent the essential knowledge, skills, and abilities for success in this role. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• NLP: intent classification, entity extraction, slot filling, rule-based dialogue + ML.
• LLM: prompting, RAG, embeddings, response evaluation, guardrails, safety filters.
• Programming: Python and/or JavaScript/TypeScript (desirable), Git, basic testing.
• Integration: MCPs, REST APIs, OAuth/SSO (concepts), webhooks, Postman.
• Data: basic/intermediate SQL, data preparation, labeling, versioning.
• Knowledge management: KB, taxonomies, content versioning, semantic search.
• Quality: conversational test cases, regression, UAT, edge case validation.
• Tools: Jira/Confluence, CI/CD (desirable)

• Analytical thinking and problem-solving (root-cause-oriented debugging).
• Technical leadership capabilities.
• Clear communication with technical and business profiles; organized documentation.
• Focus on quality and customer experience; attention to detail.
• Autonomy and ownership; ability to influence backlog prioritization.
• Teamwork and cross-functional collaboration (AI, IT, CX, operations, compliance).
• Adaptability and quick learning of emerging technologies.