AMP AI Services - Cloud AI Engineer

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. 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. 

#LI-SK1

**Visit our careers site for a list of the benefits offered in your region in addition to a competitive base salary and strong work/family programs.

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To ALL recruitment agencies: NCR Atleos only accepts resumes from agencies on the NCR Atleos preferred supplier list.  Please do not forward resumes to our applicant tracking system, NCR Atleos employees, or any NCR Atleos facility.   NCR Atleos is not responsible for any fees or charges associated with unsolicited resumes.

EEO Statement

NCR Atleos is an equal opportunity employer.  It is NCR Atleos' policy to hire, train, promote and pay associates based on their job-related qualifications, ability and performance, without regard to race, color, creed, religion, national origin, citizenship status, sex, marital status, age, physical or mental disability, sexual orientation or veteran status.