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Halian - ai expert

CDI
Indépendant
Halian
Publiée le 27 octobre
Description de l'offre

As part of our client's digital transformation strategy, we are seeking to engage an AI Specialist to embed AI across their software delivery lifecycle. The focus is not on generic AI exploration, but on practical use cases that improve speed, quality, and resilience in delivery.


The specialist will be responsible for identifying opportunities, prototyping solutions, and driving adoption of AI practices that measurably improve productivity, defect reduction, compliance alignment, and operational efficiency.








Key areas of application include



Business Analysis - Using AI to help structure stakeholder inputs, summarize discussions, and generate draft requirements. AI may also support scenario modelling to guide better decision-making.

Requirements Engineering - Applying AI tools to review documentation and user stories, detect inconsistencies or gaps, and suggest requirement structures. This supports traceability and reduces manual review effort.

Development - Leveraging AI-powered coding assistants and enhanced static analysis to accelerate development, reduce defects, and enforce coding standards.

Testing - Applying AI to optimize test coverage, generate test data, and detect anomalies in logs and performance metrics, enabling smarter and faster test cycles.

Documentation - Automating initial drafts of technical documentation (e.g., runbooks, API specs) and keeping them up to date as systems evolve.

Maintenance & Operations - Using Aiops techniques (log analysis, anomaly detection, predictive alerting) to reduce incident resolution time and improve system reliability.






Profile



We are looking for a hands-on practitioner with expertise in applying AI techniques (ML, NLP/LLMs) within delivery contexts, combined with experience in MLOps practices for deploying and managing AI-driven solutions.

A solid understanding of the software delivery lifecycle, ideally in regulated or financial services environments, is essential.

Familiarity with AI governance, prompt engineering practices, and change management will be considered advantageous.

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