Ai Architect

The

Senior AI Architect

will be responsible for defining the technological vision and leading the implementation of next‑generation Artificial Intelligence architectures. This role combines deep technical expertise, strategic thinking, and strong business alignment, ensuring that AI/GenAI solutions are scalable, secure, and deliver real impact.

Key Responsibilities

Architecture & Strategy

Design the

target architecture for AI ecosystems , including

Copilots/Agents, Azure OpenAI, AI Search, data platforms, integrations, and pipelines , ensuring end‑to‑end alignment with customer objectives.

Define

technical standards, guardrails, security practices, domain blueprints, and architectural guidelines , ensuring cross‑organizational consistency.

Translate business needs into structured technical solutions, leading

workshops, discovery sessions, and technical assessments .

Assess trade‑offs between performance, cost, risk, and complexity

when defining AI/GenAI solutions.

Technical Design & Implementation

Lead the design of

scalable, secure, high‑performance AI/GenAI architectures .

Select the appropriate technologies, frameworks, and models (LLMs, RAG, vector DBs, multi‑agent systems, MLOps, automation tooling).

Build and validate

PoCs and reference architectures

to accelerate AI adoption.

Integrate models, agents, and data pipelines with

APIs, microservices, core business applications, and enterprise data sources .

Governance, Quality & Security

Establish principles for

technical security, data isolation, compliance, observability, and model governance .

Ensure adherence to best practices in

performance, resilience, scalability, and privacy .

Define mechanisms for

control, auditability, and continuous improvement

of AI architectures in production.

Work closely with IT and Security teams

to ensure consistent integration with the customer’s enterprise architecture.

Ensure architectural consistency across multiple AI use cases and domains , particularly in large‑scale AI programs.

Technical Leadership & Collaboration

Act as a

technical authority

for internal and external stakeholders, including Data, Engineering, Product teams, and C‑level leadership.

Mentor Data Scientists, ML Engineers, and Software Engineers, promoting technical excellence and best practices.

Support

pre‑sales, RFPs, solution proposals, and technology vision

for strategic clients.

Profile

6–10 years of experience in software development, solution architecture, data engineering, or AI.

Solid experience in

AI/ML and GenAI , including LLMs, pipelines, RAG, and enterprise integration.

Strong knowledge of ML frameworks such as

TensorFlow, PyTorch, Scikit‑learn .

Significant experience with

Azure (preferred), AWS or GCP , CI/CD, Docker/Kubernetes, and microservices.

Strong understanding of

AI‑related security , cloud architectures, and MLOps practices.

Excellent communication skills, both technical and non‑technical.

Proven experience in

technical leadership and architectural standards definition .

About Inetum

Inetum is a European leader in digital services. Inetum’s team of 28,000 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 2.5 billion euros in 2023.

Additional Information

Experience in technology consulting and client interaction.

Certifications such as

Azure AI Engineer / Solution Architect, AWS ML Specialist, Google Cloud ML .

Knowledge of architecture frameworks:

TOGAF, DDD, Clean Architecture, SAFe .

Participation in conferences, talks, or

thought leadership

initiatives.

Overview

#J-18808-Ljbffr