Artificial Intelligence Engineer

• Minimum number of years of experience in this position or equivalent positions:

o Senior: >5 years

o Medior: >3 years

o Junior: >1 year

• Minimum requirements

Substantial and practical experience and knowledge of products and techniques:

o Knowledge of Chatbots, AI technology

o Knowledge based on projects in the Chatbot AI or UX domain

• General skills, knowledge of products and techniques:

o Affinity with agile development and design systems

o Affinity with agile methodology and Scrum

o Understanding of design thinking and agile working methods

o Knowledge of DevOps and CI/CD pipelines

o Basic knowledge of ITIL or similar methodologies

o Knowledge of security principles: Understanding of security in frontend development (XSS, CSRF), general principles (input validation, audit logging), API security (rate-limiting), and best practices in DevOps.

o Competencies in architecture and performance: Proficiency in event-driven, cloud-native, and network architectures, and an affinity for scalability and performance optimization.

o Understanding of AI and NLP (theory): Basic knowledge and insight into NLP architectures, tokenization, cost management, Python with AI ecosystems (Transformers, LangChain), open-source LLMs, and basic integrations.

o Ethical and regulatory sensitivity: Affinity with GDPR, ethics in AI, information security, access management, and digital government services. o Competencies in UX and communication: Insight into UX for conversational interfaces, accessibility, information architecture, content strategy, and skills in written/oral communication with clients.

o Management and methodologies: Understanding of organizational and decision-making processes, solution- and service-oriented thinking, administrative accuracy, and user management.

o Management and technical methodologies: Version control via Git/branching

o Frontend development: Thorough knowledge of HTML5, CSS3, and JavaScript, experience with Vue.js/React, responsive and accessible interfaces (WCAG), use of build tools (Webpack, Vite), component-based development (Vuex, Redux), styling libraries (Tailwind, Bootstrap).

o Backend development: Development in Java (Spring Boot) and Python (LangChain), integration of LLM APIs, REST/GraphQL endpoints, database management (SQL, NoSQL), authentication/authorization (OAuth2, JWT), unit/integration tests. o DevOps and infrastructure: CI/CD integration, containerization (Docker, OpenShift), cluster/namespace management, configuration pipelines (GitLab, ArgoCD), monitoring/alerting, logging (ELK), Infrastructure as Code, secrets management, microservices/AI deployment, backup strategies, troubleshooting.

o AI and LLM expertise (practical): Integration of LLMs, development with LangChain, prompt engineering, RAG architectures, output validation, AI security, benchmarking, governance, guardrails (NeMo), embeddings/vector search.

o Conversation design: Dialogue design, tools (Botpress, Voiceflow, Rasa), annotation/dataset training, copywriting, feedback analysis, tone of voice, collaboration with AI experts, testing flows, iteration/A/B testing, documentation. o Service management: Following up on SLAs/KPIs, organizing meetings, complaint handling, stakeholder management, reporting, support coordination, needs evaluation, service catalogs, escalation management.

Support and communication: Registration/handling of inquiries, ticketing systems (JIRA, ServiceNow), categorization/prioritization, basic tool knowledge, escalation to higher levels, support testing, customer-friendly communication, FAQs, onboarding, feedback collection.