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Job Description
As a Senior AI/ML Engineer, you will:
- Design, develop, and deploy scalable AI, Machine Learning, and Generative AI solutions for enterprise applications.
- Build intelligent automation solutions, predictive analytics models, incident prediction systems, root cause analysis engines, and AI-powered knowledge assistants.
- Develop production-grade Python applications, APIs, and microservices to expose AI capabilities across enterprise platforms.
- Design and implement robust data ingestion, preprocessing, feature engineering, and transformation pipelines for large-scale datasets.
- Integrate AI/ML models into Azure DevOps CI/CD pipelines, enabling automated model building, testing, deployment, and monitoring.
- Build and maintain MLOps pipelines to support continuous model training, validation, deployment, versioning, and lifecycle management.
- Collaborate with DevOps, platform engineering, data engineering, and product teams to deliver reliable, scalable AI solutions.
- Optimize AI models for accuracy, scalability, performance, and operational efficiency within enterprise environments.
- Ensure AI solutions comply with enterprise governance, security, audit, and regulatory standards.
- Participate in architecture discussions, technical design reviews, and continuous improvement initiatives for AI platforms.
What You Bring to the Table:
- 6–8 years of experience in Python development, AI/ML engineering, or enterprise software development.
- Strong hands-on expertise in Python for developing scalable backend applications and AI solutions.
- Experience designing, training, validating, deploying, and optimizing Machine Learning and Deep Learning models.
- Practical experience building Generative AI applications, AI Agents, intelligent automation solutions, or conversational AI systems.
- Strong knowledge of Azure cloud services and Azure DevOps for enterprise application delivery.
- Experience implementing CI/CD pipelines and MLOps workflows for AI model deployment and lifecycle management.
- Strong understanding of data engineering concepts including data preprocessing, feature engineering, and pipeline orchestration.
- Experience developing RESTful APIs and microservices to expose AI capabilities.
- Familiarity with enterprise DevOps tools such as Azure DevOps, Nexus, Ansible, and related automation frameworks.
- Strong analytical, problem-solving, communication, and stakeholder management skills.
You Should Possess the Ability to:
- Design end-to-end AI solutions from concept through production deployment.
- Build scalable, maintainable, and secure Python applications for enterprise environments.
- Integrate AI capabilities seamlessly into DevOps and CI/CD ecosystems.
- Design and maintain production-ready MLOps pipelines supporting continuous delivery of AI models.
- Translate complex business challenges into practical AI-driven solutions.
- Collaborate effectively with business stakeholders, architects, DevOps engineers, and data teams.
- Monitor, troubleshoot, and continuously improve AI model performance in production.
- Ensure enterprise-grade governance, security, compliance, and operational excellence throughout the AI lifecycle.
What We Bring to the Table:
- Opportunity to work on enterprise-scale AI, Machine Learning, and Generative AI transformation initiatives.
- Exposure to modern cloud-native architectures, MLOps platforms, and Azure DevOps ecosystems.
- Collaborative environment involving AI engineers, cloud architects, DevOps specialists, and business stakeholders.
- Challenging projects focused on intelligent automation, predictive analytics, and enterprise AI innovation.
- Opportunities for continuous learning, technical leadership, and professional growth.
- A culture that values innovation, engineering excellence, and knowledge sharing.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Giftson Paul Davidson
Phone: +31 20 369 0609 ; Extn : 151
E-mail: giftson.p@stafide.nl
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/
Key Responsibilities
Design, develop, and deploy scalable AI, Machine Learning, and Generative AI solutions for enterprise applications.