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 () 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:

- Bachelor’s or master’s 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. Postgre

SQL, SQL Server, or Mongo

DB) 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 web services.
- 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 Tensor Flow, 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.