Solution Architect (AI / ML)

For more than 20 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI driven digital transformation. Since 2001, we have grown into a full service digital consulting company with 5500+ professionals working on a worldwide ambition. Fuelling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high quality way of working that inspires all we do.

We welcome all individuals and evaluate solely on the quality of their work and teamwork.

Experienced Senior Software Engineer specialized in full-stack application development with expertise in artificial intelligence to join our team. This role combines deep technical software engineering skills across frontend and backend technologies with specialized knowledge in AI / ML technologies to design, develop, and deploy intelligent systems at scale.

We are looking for an experienced

Senior Solution Architect

with deep expertise in

AI, Machine Learning, Generative AI, and Agentic AI

to join our team. This is a senior technical leadership role focused on designing, developing, and scaling AI / ML solutions for complex enterprise environments across various industries.

Project Leadership :

Define project scope, resource planning, risk management, and delivery timelines.

Technical Mentorship :

Provide guidance and mentorship to engineering and data science teams.

Represent the organization in workshops, conferences, and technical forums.

TensorFlow, PyTorch, scikit-learn) and GenAI tools.

~ Familiarity with LLMs, Retrieval-Augmented Generation (RAG), vector databases, multi-agent systems, evaluations.

~ Proficient in Python.

~ Excellent communication skills, including experience engaging with executive-level stakeholders.

~ Knowledge of cloud platforms (AWS, Azure, GCP), including MLOps practices.

Experience with data engineering, large-scale data infrastructure, and data governance.

Understanding of AI project economics and business case development.