Asks for

The ad says“Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.”
The ad says“Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.”
The ad says“Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.”
The ad says“Proven technical leadership and hands-on delivery across MLOps/LLMOps, AI/ML platforms, cloud architecture, infrastructure automation, model operationalization and production operations.”
The ad says“Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.”
The ad says“Strong knowledge of security, data privacy, model risk, responsible AI, resilience, disaster recovery and regulatory requirements relevant to enterprise AI.”
The ad says“Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.”
The ad says“Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.”
The ad says“Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.”
The ad says“Proven technical leadership and hands-on delivery across MLOps/LLMOps, AI/ML platforms, cloud architecture, infrastructure automation, model operationalization and production operations.”
The ad says“AI platform strategy and architecture: Lead the evolution of the AI platform landscape, including MLOps, LLMOps, Azure AI services, AI Foundry, Databricks, the SG Agentic Platform and related engineering capabilities. Define and implement target patterns that enable secure and scalable industrialization.”
The ad says“Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.”
The ad says“As our new AI Technical Lead, you will provide the technical leadership and hands-on MLOps expertise required to define, operationalize, validate and scale AI solutions across Ayvens. You will support strategic AI decisions while remaining directly involved in the MLOps implementation layer, covering technology choices, architecture, platform capabilities, infrastructure as code, integration, deployment, technical staffing and production readiness. You will translate business and governance needs into working MLOps patterns and ensure that AI solutions are secure, interoperable, scalable, maintainable and aligned with the target technology landscape.”
The ad says“Strong knowledge of security, data privacy, model risk, responsible AI, resilience, disaster recovery and regulatory requirements relevant to enterprise AI.”
The ad says“Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.”
The ad says“Strong knowledge of security, data privacy, model risk, responsible AI, resilience, disaster recovery and regulatory requirements relevant to enterprise AI.”
The ad says“Strong knowledge of security, data privacy, model risk, responsible AI, resilience, disaster recovery and regulatory requirements relevant to enterprise AI.”
The ad says“Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.”
The ad says“Strong knowledge of security, data privacy, model risk, responsible AI, resilience, disaster recovery and regulatory requirements relevant to enterprise AI.”
The ad says“Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.”
The ad says“Infrastructure as code and cloud automation: Strong practical experience designing modular Terraform structures, reusable modules, environment configurations, state management and automated cloud deployments. Experience integrating infrastructure as code into secure CI/CD pipelines is required.”
The ad says“Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.”

At Ayvens, progress starts with you.

Our ambitions to shape the future of sustainable mobility are powered by our talent. Join us, and get better with every move.

At Ayvens we have an opening for an experienced AI Technical Lead.

What are you going to do?

As our new AI Technical Lead, you will provide the technical leadership and hands-on MLOps expertise required to define, operationalize, validate and scale AI solutions across Ayvens. You will support strategic AI decisions while remaining directly involved in the MLOps implementation layer, covering technology choices, architecture, platform capabilities, infrastructure as code, integration, deployment, technical staffing and production readiness. You will translate business and governance needs into working MLOps patterns and ensure that AI solutions are secure, interoperable, scalable, maintainable and aligned with the target technology landscape.

You will report to the Director Data Science & AI.

Your responsibilities will include:

Technical leadership and decision support: Act as the senior technical reference for AI and data science initiatives. Provide clear recommendations on architecture, platforms, build-versus-buy decisions, reuse opportunities, technical feasibility, engineering effort and delivery risks.
AI platform strategy and architecture: Lead the evolution of the AI platform landscape, including MLOps, LLMOps, Azure AI services, AI Foundry, Databricks, the SG Agentic Platform and related engineering capabilities. Define and implement target patterns that enable secure and scalable industrialization.
MLOps capacity and staffing: Assess the MLOps and platform profiles, skills, capacity and delivery model required to operationalize AI initiatives. Support workforce and sourcing decisions, challenge staffing assumptions and help structure effective collaboration between MLOps, Data Science, AI Engineering, Data Engineering, Architecture and infrastructure teams.
MLOps solution design, implementation and technical assurance: Design, configure, review and challenge the operationalization layer across model packaging, APIs, serving endpoints, integrations, cloud infrastructure, security, deployment and operations. Contribute directly to reference MLOps implementations, platform configurations, deployment pipelines and reusable operational components. Ensure solutions meet quality, resilience, performance, interoperability and maintainability expectations.
Industrialization and operations: Establish and implement engineering standards for CI/CD, testing, code quality, model and prompt evaluation, observability, monitoring, versioning, deployment, incident management, disaster recovery and lifecycle maintenance. Build and maintain reusable MLOps/LLMOps patterns for the operationalization of AI solutions.
AI governance and compliance: Provide technical input to AI governance decisions and ensure architecture, security, privacy, MRM, AI Act and internal control requirements are translated into implementable engineering controls and evidence.
Technical roadmap and investment planning: Contribute to technology roadmaps, platform investments and engineering budgets. Provide transparent estimates and options, including cost, resource implications, dependencies and trade-offs.
Stakeholder communication: Explain complex technical topics, options and risks in concise business language. Facilitate decisions with senior leaders, Product, Architecture, Security, Risk, Legal, countries and delivery teams, and document clear recommendations and ownership.
MLOps coaching and standards: Guide MLOps specialists and technical leads, promote reusable platform assets and reference architectures, and raise MLOps maturity through practical standards, platform reviews and knowledge sharing. Work closely with the AI Engineering team without owning AI application engineering delivery.

Who are you?

The ideal candidate is a senior MLOps and AI platform leader who combines deep hands-on operational expertise with strong judgment, communication and organizational influence. You can move comfortably from detailed MLOps implementation discussions to executive decision forums, and you can challenge platform, operationalization and resourcing assumptions with clarity and credibility.

Typically 10+ years of relevant experience across technology, data platforms or AI, including substantial hands-on experience leading the MLOps architecture, industrialization and operation of production AI platforms in complex international environments.
Proven technical leadership and hands-on delivery across MLOps/LLMOps, AI/ML platforms, cloud architecture, infrastructure automation, model operationalization and production operations.
Strong experience defining target architectures, technical standards and engineering roadmaps, and making pragmatic technology decisions under constraints.
Demonstrated ability to assess engineering effort, staffing needs, required profiles and delivery capacity, and to advise on internal versus external resourcing models.
Strong hands-on MLOps experience with Python, SQL, REST APIs, Git-based workflows, CI/CD, containers, model serving, monitoring, automated testing and cloud platform practices. The candidate must be able to review deployment pipelines and platform configurations, create MLOps prototypes and support production operationalization directly.
Hands-on experience with Azure and Databricks ecosystems, including Azure AI Foundry, MLflow, Unity Catalog, GitHub and agentic AI platforms. Practical experience creating and operating production-grade AI services is highly valuable.
Strong knowledge of security, data privacy, model risk, responsible AI, resilience, disaster recovery and regulatory requirements relevant to enterprise AI.

Hands-on MLOps leadership: Willing and able to work directly within the MLOps team, inspect repositories, Infrastructure-as-Code configurations and deployment pipelines, troubleshoot platform and operationalization issues, build reference MLOps implementations and turn architecture decisions into executable platform standards and reusable assets.

Production MLOps/LLMOps engineering: Demonstrated experience moving models and GenAI solutions from experimentation into production, including packaging, deployment, orchestration, evaluation, observability, rollback, versioning, performance management and ongoing support.

AI interoperability and integration: Proven experience operationalizing AI solutions through well-designed APIs, event-driven integrations, model-serving interfaces and reusable platform services. Ability to integrate AI capabilities with enterprise applications, data platforms, authentication, logging and monitoring services.

Infrastructure as code and cloud automation: Strong practical experience designing modular Terraform structures, reusable modules, environment configurations, state management and automated cloud deployments. Experience integrating infrastructure as code into secure CI/CD pipelines is required.

Excellent communication and influencing skills, with the ability to present complex technical options, costs, risks and trade-offs clearly to both executives and engineering teams.
Proven ability to lead through influence, challenge constructively, manage ambiguity and align cross-functional stakeholders across countries and central functions.
Ability to coach MLOps and platform specialists, run platform and operational-readiness reviews, and create a culture of MLOps quality, accountability and continuous improvement.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Mathematics or a related technical discipline.
Fluent English is required. Experience in mobility, leasing, financial services or another regulated industry is an advantage.

What do we offer?

We're on this journey together. By investing in professional growth, rewards and incentives, plus plenty of training and experience on the job, we create an inspiring environment for our colleagues that fosters high performance with positive impact.

Enjoy comprehensive rewards and recognition.
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Discover your talent.
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Benefit from a healthy, positive work atmosphere.
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Find a shared sense of belonging.
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Build a sustainable future.

Make your Move at AyvensAyvens provides a unique opportunity: the chance to accelerate the transition to electric, lead the way to decarbonisation and shape the industry’s digital transformation. Behind the wheel, our people make the difference, driving us towards our ambitions. Ayvens is home to the best talent in the industry – so if you’re looking for a fulfilling career with positive impact, we’d love to discuss your opportunities with us!Ready to make your move at Ayvens? Join a global leader in sustainable mobility and follow @ayvens, @lifeatayvens, and Ayvens on LinkedIn to check out what’s happening at Ayvens! Our commitmentWe’re committed to building a culture where everyone can be themselves and where everyone gets an equal chance to make their journey count. If you’d like to learn more about our DE&I journey – and how you can contribute – please find out more on Career pages of our website.

Why Ayvens?

With over 3.1 million vehicles managed across more than 40 countries, we provide full-service leasing, flexible subscription services, fleet management services and multi-mobility solutions to customers of all sizes, including large corporates, SMEs, professionals, and private individuals. By leveraging our unique position to lead the way to net zero and further shape the digital transformation of the industry, we are well-positioned to meet the evolving mobility needs of our clients and provide them with the solutions they need to thrive.

At Ayvens, we believe that our success is driven by our commitment to customer satisfaction. Our team is dedicated to delivering innovative solutions and technology-enabled services that help our customers focus on their everyday business. We’re committed to sustainable mobility and have made it a core part of our strategy. In everything we do, we’re guided by the principles of authenticity, curiosity, commitment and collaboration. We aim to foster an organisation that's diverse in people and ideas, where everyone can thrive and be themselves, no matter who they are.

Join us on this exciting journey as we continue to enable the transformation towards large scale adoption of sustainable mobility and provide our customers with the solutions they need to succeed. Follow our page for the latest updates, news, and insights.