• Lead and oversee the AI team in designing, developing, and deploying AI and machine learning models and solutions. • Define and execute the AI strategy aligned with business goals and emerging industry trends. • Collaborate with cross-functional teams including data science, engineering, product management, and business units to identify AI-driven opportunities and deliver impactful solutions. • Manage AI projects ensuring timely delivery, quality, and alignment with organizational objectives. • Mentor and develop the AI team by fostering skills growth, collaboration, and innovative thinking. • Stay abreast of the latest AI research, tools, and methodologies and assess their applicability to business problems. • Communicate complex AI concepts clearly to non-technical stakeholders to facilitate informed decision-making. • Advocate best practices for AI ethics, data privacy, and security within the organization.

- Lead and mentor a cross-functional engineering team, fostering a culture of collaboration, innovation, and continuous improvement, with a strong focus on AI adoption. - Drive the design, implementation, and evolution of AI-powered solutions, particularly AI agents, to enhance software development workflows, developer productivity, and operational efficiency. - Act as a hands-on technical leader, actively contributing to system design, code reviews, and the development of AI-driven capabilities integrated into the platform. - Identify and prioritize high-impact opportunities to leverage AI across the software development lifecycle, including code generation, testing, debugging, incident analysis, and documentation. - Architect and implement scalable and secure systems that combine traditional backend engineering with AI components (e.g., LLM integrations, RAG pipelines, agent-based workflows). - Collaborate with product, engineering, and business stakeholders to define AI use cases aligned with company goals and deliver measurable impact. - Establish best practices for building, evaluating, and maintaining AI systems in production, including observability, performance, cost control, and reliability. - Drive the adoption of AI tools and practices across engineering teams, acting as a mentor and enabler for developers to effectively leverage AI in their daily work. - Ensure that AI implementations comply with security and regulatory requirements (e.g., PCI DSS, GDPR, DORA), especially in the context of sensitive financial data. - Mitigate technical risks related to both traditional systems and AI components, ensuring platform stability, resilience, and trustworthiness. - Contribute directly to the development of high-quality, high-performance software solutions, maintaining a strong hands-on involvement. - Diagnose and resolve complex issues in production environments, including those involving AI systems and agent-based workflows. - Drive technical decision-making, balancing innovation in AI with long-term scalability, maintainability, and business impact. - Drive technical decision-making, balancing long-term scalability with immediate business needs. - Foster a culture of innovation, collaboration, and accountability across technical teams.

Role Description As an AI Engineer, you will design, develop, and deploy AI-driven solutions that solve real-world business challenges. You will work across the full AI lifecycle—from data preparation and model development to deployment, monitoring, and optimization—while collaborating closely with product managers, software engineers, and domain experts. This role is ideal for engineers with hands-on experience in machine learning and Generative AI who are passionate about building production-ready AI systems and delivering measurable business impact. AI Development & Deployment - Design, develop, and optimize machine learning and deep learning models for production environments. - Build AI-powered features and services that address customer and business needs. - Own the end-to-end AI lifecycle, including data exploration, model development, evaluation, deployment, monitoring, and continuous improvement. - Perform model evaluation, error analysis, and performance optimization to ensure reliability and accuracy. Generative AI & LLM Applications - Develop and enhance AI applications powered by Large Language Models (LLMs). - Build Retrieval-Augmented Generation (RAG) systems, semantic search solutions, and AI assistants. - Work with embeddings, vector databases, and modern AI orchestration frameworks. - Evaluate and improve model outputs for quality, relevance, latency, and user experience. Production Engineering - Deploy and maintain AI services in cloud and containerized environments. - Build scalable APIs and inference pipelines for real-time and batch processing workloads. - Monitor AI systems in production and troubleshoot performance or reliability issues. - Collaborate with engineering teams to integrate AI capabilities into customer-facing products. Collaboration & Innovation - Partner with Product, Engineering, Data, and Customer Success teams to translate business requirements into AI solutions. - Contribute to technical discussions, design reviews, and AI best practices. - Stay up to date with emerging AI technologies and recommend practical innovations that create business value. Qualifications - 2–4 years of professional experience in Artificial Intelligence, Machine Learning, Data Science, or related engineering roles. - Proven experience developing and deploying AI or machine learning solutions into production environments. Requirements - Strong proficiency in Python. - Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow. - Solid understanding of machine learning fundamentals, model evaluation techniques, and performance optimization. - Experience building AI applications using Large Language Models (LLMs). - Familiarity with Retrieval-Augmented Generation (RAG), embeddings, and vector search concepts. - Experience building APIs using FastAPI, Flask, or similar frameworks. - Understanding of software engineering best practices, version control, and testing methodologies. - Experience deploying AI models into production environments. - Familiarity with Docker and cloud platforms such as AWS, Azure, or GCP. - Understanding of monitoring, observability, and AI system reliability. - Strong analytical and problem-solving abilities. - Excellent communication and collaboration skills. - Ability to work effectively in a fast-paced, cross-functional environment. Preferred Qualifications - Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks. - Experience working with vector databases such as Pinecone, Qdrant, ChromaDB, Weaviate, or FAISS. - Exposure to agent-based AI systems and workflow automation. - Experience with MLOps practices, CI/CD pipelines, and model monitoring. - Experience with computer vision, multimodal AI, recommendation systems, or NLP applications. - Familiarity with self-hosted open-source models and modern inference frameworks. What Success Looks Like - Deliver production-grade AI solutions that create measurable business impact. - Contribute to Lucidya's next generation of AI-powered products and capabilities. - Improve model performance, reliability, and scalability across AI services. - Collaborate effectively with engineering and product teams to bring AI innovations to market. - Continuously expand Lucidya's AI capabilities through practical experimentation and execution.

Role Description We are seeking an experienced and highly skilled AI Engineering Team Lead (Agents & Developer Productivity) to join our technology team at Revup Payments, a leading global Payment Orchestrator. In this role, you will lead a team of talented engineers while remaining hands-on, driving the design, development, and adoption of AI-powered solutions, particularly AI agents to enhance our software development lifecycle and internal engineering workflows. Your mission will be to embed AI capabilities across the organization, improving developer productivity, code quality, and delivery speed. You will work closely with engineering, product, and platform teams to identify high-impact opportunities where AI can optimize processes such as: - Code generation - Testing - Incident analysis - Integration of payment methods (including card processing, eWallets, and Alternative Payment Methods) Your technical expertise and leadership will be pivotal in ensuring our platform remains robust, scalable, and innovative, while evolving our engineering practices through the effective use of AI. Qualifications - Bachelor's degree in Computer Science, Software Engineering, or a related field (equivalent experience is valued). - Collaborative mindset with the ability to work cross-functionally with Product, DevOps, and Security teams. - Over 7 years of professional experience in software engineering, including: - 6+ years of experience with Java as the primary programming language. - 4+ years leading hybrid engineering teams (in-house and outsource). - Proven experience in the payment industry, fintech, banking, or financial services. - Hands-on experience with AI-assisted development tools and coding agents. - Strong ability to apply AI to real engineering problems. - Deep expertise in software architecture, microservices, and cloud-based solutions in AWS. - Deep understanding and practical application of Object-Oriented Programming (OOP) principles. - Advanced proficiency in Web/API environments. - Proficiency in database design and optimization. - Familiarity with DevOps practices, CI/CD pipelines, and containerization technologies. - Excellent problem-solving skills and the ability to make data-driven decisions. - Excellent communication skills, with the ability to educate and mentor engineers in AI adoption. - High level of ownership and agency. Requirements - Experience with NodeJs or Python is an advantage but not mandatory. - Relevant certifications in cloud platforms, such as AWS. - Experience with modern Java frameworks and native compilation using GraalVM. Benefits - Competitive salary and comprehensive benefits package. - Opportunity to shape HR strategy for a global, innovative fintech company. - Professional development opportunities and resources. - A collaborative, inclusive, and dynamic work culture. - Full Remote Work. - Growth and career development with personalized internal training and an annual budget for external learning opportunities. - Flexible schedule with flextime and the option of working full remote or from our Barcelona office. - 25 days of vacation plus your birthday off, with flexible vacation options. - Unique office perks, including free coffee, fresh fruit, snacks, and a game room. - Additional benefits include ticket restaurant and nursery vouchers.