Senior AI/ML Engineer (ID: 3865)

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.