Artificial Intelligence Engineer

TechTalent Resourcing; Brussel; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

TechTalent Resourcing seeks a senior professional to lead chatbot AI projects and UX initiatives, blending backend Java Spring Boot with LangChain integrations. You will shape scalable architectures, ensure secure API practices, and collaborate with clients to deliver AI-driven conversational solutions.

Ideal candidates bring 5+ years in related roles, strong Agile/ Scrum experience, GDPR awareness, and a track record in designing user-centric AI systems.

Qualifications

• Seasoned pro with 5+ years in related roles.
• Experience with Chatbots AI projects and UX work.
• Strong Agile, Scrum, and design systems knowledge.
• DevOps CI/CD and Git workflows understanding.
• Security-minded frontend and API practices.
• Familiarity with NLP, LLMs, and LangChain.
• GDPR ethics and responsible AI awareness.
• Excellent UX and client communication skills.
• Backend Java Spring Boot and Python LangChain experience.
• Testing: unit/integration practices.

Connaissances

Chatbots & AI

Chatbot UX

Agile & Scrum

Design thinking

DevOps CI/CD

ITIL basics

Frontend security

Architecture performance

AI NLP basics

GDPR ethics in AI

UX communication

Git version control

Java Spring Boot

Python LangChain

REST & GraphQL

OAuth2/JWT

Unit/integration tests

Outils

Git

Docker

OpenShift

GitLab

ArgoCD

ELK

LangChain

Rasa

Botpress

Voiceflow

Description du poste

• Minimum number of years of experience in this position or equivalent positions:
  • Senior: >5 years
  • Medior: >3 years
  • Junior: >1 year
• Substantial and practical experience and knowledge of products and techniques:
  • Knowledge of Chatbots, AI technology
  • Knowledge based on projects in the Chatbot AI or UX domain
• General skills, knowledge of products and techniques:
  • Affinity with agile development and design systems
  • Affinity with agile methodology and Scrum
  • Understanding of design thinking and agile working methods
  • Knowledge of DevOps and CI/CD pipelines
  • Basic knowledge of ITIL or similar methodologies
  • 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.
  • Competencies in architecture and performance: Proficiency in event-driven, cloud-native, and network architectures, and an affinity for scalability and performance optimization.
  • 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.
  • Ethical and regulatory sensitivity: Affinity with GDPR, ethics in AI, information security, access management, and digital government services.
  • Competencies in UX and communication: Insight into UX for conversational interfaces, accessibility, information architecture, content strategy, and skills in written/oral communication with clients.
  • Management and methodologies: Understanding of organizational and decision-making processes, solution- and service-oriented thinking, administrative accuracy, and user management.
  • Management and technical methodologies: Version control via Git/branching
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.