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Lead Software Engineer

Lead Software Engineer

Michelin
Early Applicant
  • Posted 6 days ago
  • Be among the first 10 applicants

Job Description

Lead Software Engineer

- - - - - - - - - - - -

Mission

Move from AI exploration to AI adoption by accelerating the software development lifecycle through measurable impact, real usage, and scaled adoption-delivering tangible results powered by the DRIVE program.

Key Expected AchievementsAs part of a strategic initiative on Generative AI, you will design, build, and industrialize high visibility GenAI solutions.


You will work closely with innovation, data, and IT teams to deliver robust, scalable, and secure AI capabilities that integrate seamlessly with enterprise systems​

Key Responsibilities:

. Design and develop AI powered applications integrating Large Language Models (LLMs), including RAG, embeddings, and agent-based components.

. Define and contribute to scalable GenAI architectures, ensuring robustness, performance, and industrial readiness.

. Implement APIs, microservices, and AI pipelines within an industrial cloud environment.

. Support client teams through scoping, technical expertise, architecture reviews, audits, and best practice guidance.

. Ensure solution quality, security, compliance, and observability, following governance and risk management standards.


Required Profile:

. Strong backend engineering experience in Python, Node.js, or Java.

. Proficiency with GenAI frameworks such as LangChain, LlamaIndex, Hugging Face, and OpenAI API.

. Hands on exposure to at least one major cloud platform (Azure, AWS, or GCP) and experience with demanding production grade industrial environments.

. Ability to operate effectively in large enterprise ecosystems: structured communication, rigor, and a strong service mindset.

. Experience with RAG architectures, vector databases, and MLOps pipelines is a strong plus.


Team Life & Ways of Working:

. Embrace and respect Agile rituals, contributing actively to continuous improvement of team processes and collaboration.

. Participate in workload estimation for backlog items, challenging complexity and scope when needed.

. Contribute to sprint planning and allocation of tasks, supporting the delivery of incremental value and modernization of components (Evergreen approach).


Behavioural Skills:

Planning & organizing,

Teamwork & Collaboration,

Customer Focus,

Continuous learning

Ability to rapidly learn and take advantage of new concepts, business models, and technologies

Working with internal and external stakeholders in an international environment.

Product approach mindset

Experience - 5-7 years

Key Skills

LangChain

RAG embeddings

Vector databases

Hugging Face

Cloud environment

Agent-based components

MLOps pipelines

OpenAI API

AI pipelines

LlamaIndex

Large Language Models (LLMs)

RAG architectures

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