Cloud AI Engineer

Title: Cloud AI Engineer

Grade: 10

Location: Hyderabad

About NCR Atleos:

NCR Atleos (NYSE: NATL) is a global technology company creating exceptional self-service banking experiences. We offer all of the services, software and hardware solutions needed for a comprehensive self-service channel. NCR Atleos (www.ncratleos.com) is headquartered in Atlanta, Georgia.

Job Description

Responsibilities:

AI Engineering & Integration

• Design, develop, and deploy Agentic automations using LLMs, AI/ML models, across multi-cloud platforms.
• Implement AI-driven automation and API integrations for operational efficiency and predictive maintenance.
• Collaborate with data scientists, product teams, and operations to integrate AI into enterprise workflows.

Cloud Architecture & Multi-Cloud Strategy

• Implement multi-cloud solutions (AWS, Azure, GCP) for AI workloads with interoperability in mind.
• Develop Infrastructure as Code (IaC) using tools like Terraform, Azure Service Operator or Pulumi for scalable deployments.
• Optimize cost, performance, and resilience across heterogeneous components, services and cloud environments.

Site Reliability Engineering

• Follow SRE principles: reliability, observability, and performance for AI systems and cloud deployments.
• Implement CI/CD pipelines, automated testing, and monitoring frameworks for AI services.
• Drive incident response, root cause analysis, and continuous improvement for production systems.

Security & Compliance

• Ensure AI solutions meet security, compliance, and ethical standards.
• Implement cloud-native security controls and data governance for sensitive AI workloads.

Requirements:

• Bachelors or masters degree in computer science, Data Science, or a related field.
• Strong proficiency in one of object-oriented programming languages such as Java, C#, or C++.
• Fluent in at least one database technology (e.g. PostgreSQL, SQL Server, or MongoDB) with experience in designing scalable database architecture
• Extensive experience with Java, Python, and distributed systems design (e.g., microservices architecture).
• Strong debugging and Integration skills with proven ability to troubleshoot complex systems and ensure seamless interoperability across services.
• 5+ years of experience working with API integration, RESTful webservices.
• Experience developing, deploying containerized (Kubernetes and Docker) services and cloud resources (Azure/GCP/AWS).
• Hands-on experience with IaC tools (Terraform, Ansible) and CI/CD pipelines.
• Proficient in scripting and data modeling using Python or R.
• Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Experience with large language models (LLMs) such as GPT, BERT, or similar.
• Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
• Proficient with Git, Github Actions, rapid prototyping and deployment.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills and ability to work in a team environment.

Preferred Qualifications:

• Multi-Cloud Expertise: Proven experience in cloud migration and multi-cloud strategy.
• AI Integration: Hands-on with LLM integration into enterprise applications.
• Certifications: Cloud (AWS/Azure/GCP) and AI/ML certifications.
• Familiarity with NLP, computer vision, and conversational AI.
• Knowledge of AI ethics, compliance standards, and data privacy regulations.