Senior AI​/ML Engineer

• 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 Dev Ops 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 Dev Ops, 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.

• 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 Dev Ops 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 Dev Ops tools such as Azure Dev Ops, Nexus, Ansible, and related automation frameworks.
• Strong analytical, problem‑solving, communication, and stakeholder management skills.

• 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 Dev Ops 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, Dev Ops 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.

• Opportunity to work on enterprise‑scale AI, Machine Learning, and Generative AI transformation initiatives.
• Exposure to modern cloud‑native architectures, MLOps platforms, and Azure Dev Ops ecosystems.
• Collaborative environment involving AI engineers, cloud architects, Dev Ops 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.

Want to discuss this opportunity in more detail? Feel free to reach out.