AI Engineer

Company Description

Organization

Our Mission Statement

Digital and human resources at the center of the sustainable development of our society.

In a world of continuous transformation, accelerated by technological developments and societal challenges, it is necessary to adapt in an ongoing, agile way to meet the challenges of the future.

About Inetum

Inetum is a European leader in digital services. Inetum’s team of 27,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good.

Present in 19 countries with a dense network of sites, Inetum partners with major software publishers to meet the challenges of digital transformation with proximity and flexibility. Driven by its ambition for growth and scale, Inetum generated sales of 2.4 billion euros in 2024.

For further information, please visit www.inetum.com

Job Description

Designing, developing, and implementing machine learning models using Python and frameworks such as PyTorch, ensuring that the models are robust, scalable, and optimized for performance.
Building and orchestrating workflows for AI agents using agentic frameworks like LangChain, LiveKit, and OpenAIAgentsSDK, including solutions such as enterprise chatbots, internal AI productivity assistants, document intelligence systems, and automated agent-driven workflows.
Designing and validating agent behavior using MCP (Model Context Protocol), Guardrails, and structured instructions for agents, ensuring safety, consistency, and compliance.
Leveraging AWS Bedrock as the primary service for LLMs, integrating foundational models and optimizing inference performance within enterprise AI systems, as well as enabling RAG architectures with modern embedding and information retrieval techniques.
Designing and automating high-level AI workflows using tools like n8n, facilitating rapid prototyping, integration, and automated orchestration of multi-step workflows based on agents or LLMs.
Using OpenWebUI (or similar LLM interface frameworks) for testing, iterating, and managing LLM workflows and agent-driven workflows in on-prem or hybrid environments.
Utilizing AWS SageMaker for efficient and scalable training and deployment of machine learning models.
Developing and managing big data processing workflows using Apache Spark on AWS EMR, optimizing data processing tasks to efficiently handle large datasets, enabling rapid feature extraction and preprocessing required for machine learning models.

Qualifications

Bachelor’s or master’s degree in computer science, Data Science, Engineering, or a similar technical field.
Over 4 years of experience in machine learning or AI engineering, including demonstrated experience in developing and deploying models at scale.
Strong programming skills in Python.
Advanced knowledge in NLP and LLM models.
Hands-on experience with AWS services (SageMaker, Bedrock, EMR) for end-to-end AI pipelines, or equivalent experience on other similar cloud platforms.
Ability to write clean, maintainable, and efficient code, adhering to software engineering best practices (e.g., versioning, testing, CI/CD).
Strong analytical and problem-solving skills.

Benefits

Additional Information

Full access to foreign language learning platform
Personalized access to tech learning platforms
Tailored workshops and trainings to sustain your growth
Medical insurance
Meal tickets
Monthly budget to allocate on flexible benefit platform
Access to 7 Card services
Wellbeing activities and gatherings

Working model: hybrid, 2 days/office

Key Skills

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