AI Tech Lead

Tech Riders

. Work across the entire AI project lifecycle: ideation, experimentation, scaling, and industrialization .

Posted 9/19/2026full-timeParis • FranceSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in AI project lifecycle management, including ideation, experimentation, and industrialization, while ensuring compliance with AI ethics and standards. Proficient in optimizing AI model performance and resource consumption, with a strong focus on environmental impact and scalability.

Highest-signal resume keywords

AI Project Lifecycle ManagementGenerative AI Models ExpertiseAPI Integration and DeploymentCompliance Standards KnowledgePerformance Optimization Strategies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonJavaAI Development Best PracticesProduction AI ArchitecturesGPU InfrastructuresPerformance OptimizationModel Control and Audit MechanismsRAG TechniquesCloud DeploymentVersion Control

Soft Skills

Excellent CommunicationOrganizational SkillsCollaboration with Multidisciplinary Teams

Tools & Technologies

Commercial LLMsOpen-Source LLMsCloud InfrastructuresOn-Premise Infrastructures

Industry Keywords

AI EthicsEU AI ActGDPRCybersecurityBanking SectorInsurance Sector

Tech Stack

Tools & technologies

CloudJavaPython

About the role

Key responsibilities & impact

Work across the entire AI project lifecycle: ideation, experimentation, scaling, and industrialization
Define and promote AI technical standards and best practices relating to code quality, performance, security, maintainability, API integration, and cloud deployment
Provide AI technical expertise and challenge architecture and modeling decisions
Select and oversee the use of commercial, open-source, and cloud-based LLMs
Guide the implementation of effective RAG techniques
Ensure the performance, compliance, security, adoption, and business operation of AI models
Ensure the scalability, robustness, and interoperability of models with existing systems
Optimize performance and resource consumption
Contribute to defining environmental KPIs related to the use of AI models, including energy efficiency, carbon footprint, and GPU resource utilization
Analyze KPI trends and propose optimization initiatives to improve energy efficiency and reduce environmental impact
Maintain continuous awareness of advances in AI and propose innovative technical improvements
Support cross-functional teams of Developers, Data Scientists, and Architects in applying development and industrialization best practices
Work with the software vendor and operations provider to deploy and integrate AI models into the client’s cloud and on-premise infrastructures
Propose and oversee technical and methodological improvements to optimize the integration and deployment of AI models

Requirements

What you’ll need

7+ years of experience as an AI Tech Lead, Lead Data Engineer, or Senior ML Engineer
Demonstrated ability to manage complex technology projects and collaborate with multidisciplinary teams
Strong knowledge of AI project processes: ideation, experimentation, and industrialization
Good knowledge of AI development best practices: code structuring, testing, version control, and deployment
Good knowledge of compliance standards: AI ethics, the EU AI Act, GDPR, and cybersecurity
Knowledge of related governance practices, particularly model control and audit mechanisms
Significant experience designing and implementing production AI architectures
Experience with API integration and deployment on cloud and on-premise infrastructures
Proven expertise in generative AI models, particularly Mistral, Gemini, Qwen, and DeepSeek
Experience evaluating, selecting, and optimizing models based on performance, security, compliance, and environmental impact
In-depth knowledge of GPU infrastructures and performance optimization strategies for training and inference
Proficiency in multiple programming languages, including Python and Java
Ability to challenge and unite senior technical professionals, including Developers, Data Scientists, and Architects
Excellent communication and organizational skills
Knowledge of the banking and insurance sectors is a plus

Benefits

Comp & perks

Healthy work-life balance
Career development through the acquisition of new areas of expertise
Fair compensation
Team cohesion
Transparency
Knowledge sharing and shared prosperity