Software Engineer AWS, Data Pipelines & AI Integration

Geaerospace; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Geaerospace is seeking a versatile software engineer with cross-domain expertise in full-stack development, cloud-native design, and data engineering to deliver scalable, secure digital solutions.

You will work with system engineers, data scientists, frontend developers, and platform teams to build and enhance shared platforms, data pipelines, and intelligent applications that align with enterprise architecture and business priorities.

Qualifications

• Hands-on production AWS experience required.

Responsibilities

• Design, build, and maintain end-to-end software and data solutions across cloud and distributed environments.
• Collaborate with cross-functional teams to deliver solutions aligned with enterprise architecture, shared platforms, and product priorities.
• Contribute to technical architecture decisions, including scalability, security, maintainability, and performance trade-offs.
• Develop and optimize data pipelines, integrations, APIs, and application services.
• Support AWS-based application, data, and AI/ML workloads, including orchestration, monitoring, and security.
• Integrate AI/ML capabilities into products and business workflows, including model deployment, inference pipelines, and monitoring.
• Partner with DevOps teams to improve CI/CD, automation, observability, and operational resilience.
• Write clean, secure, and maintainable code across frontend, backend, and data layers.
• Troubleshoot production issues, identify root causes, and implement durable fixes.
• Support security, compliance, and governance requirements, including standards such as NIST, GDPR, and SOX where applicable.
• Stay current on emerging technologies and contribute ideas that improve products, platforms, and engineering practices.
• Master’s degree in Computer Science or a STEM field.
• Relevant working experience in software engineering, data engineering, or related technical roles.
• Must have hands-on experience with Lambda, S3, API Gateway, ECS/EKS, IAM, CloudWatch, Step Functions.
• Experience with backend development using Python, Java, and related frameworks.
• Experience designing or supporting data pipelines, ETL/ELT processes, and integrations.
• Familiarity with CI/CD, automated testing, containerization, and cloud-native tools such as Git, Docker, Kubernetes, Gradle, or Maven.
• Understanding of secure engineering practices and compliance considerations in enterprise environments.
• Experience with AI/ML deployment, integration, or monitoring.
• Experience with API orchestration, MCP-based integrations, or connected system architectures.
• Knowledge of technical data domains and enterprise data architecture.
• Ability to work effectively across teams, communicate clearly, and adapt to changing priorities.

Skills

Full-stack development

Cloud-native design

Data engineering

Security practices

CI/CD

Observability

Python

Java

API development

AI/ML deployment

Education

Master’s degree in Computer Science or STEM field

Tools

AWS Lambda

S3

API Gateway

ECS/EKS

IAM

CloudWatch

Step Functions

Docker

Kubernetes

Git

Gradle or Maven

Job description

We are seeking a versatile software engineer with experience across full-stack development, technical architecture, and data engineering to help deliver scalable, secure, and modern digital solutions. In this role, you will work closely with system engineers, data engineers, AI/ML specialists, frontend developers, and platform teams to build and enhance shared platforms, data pipelines, and intelligent applications that align with enterprise architecture and business priorities.

This role is ideal for someone who is comfortable moving across application development, cloud-native design, and data workflows, while contributing to secure and compliant engineering practices.This role is home-based, preferably located in Germany, and requires occasional travel as needed for business and team collaboration. This role is intended for candidates with hands-on production AWS engineering experience. Experience limited to coursework, internships, or personal projects alone is not sufficient. Candidates should have demonstrated ownership of systems in production environments.

• Design, build, and maintain end-to-end software and data solutions across cloud and distributed environments.
• Collaborate with cross-functional teams to deliver solutions aligned with enterprise architecture, shared platforms, and product priorities.
• Contribute to technical architecture decisions, including scalability, security, maintainability, and performance trade-offs.
• Develop and optimize data pipelines, integrations, APIs, and application services.
• Support AWS-based application, data, and AI/ML workloads, including orchestration, monitoring, and security.
• Integrate AI/ML capabilities into products and business workflows, including model deployment, inference pipelines, and monitoring.
• Partner with DevOps teams to improve CI/CD, automation, observability, and operational resilience.
• Write clean, secure, and maintainable code across frontend, backend, and data layers.
• Troubleshoot production issues, identify root causes, and implement durable fixes.
• Support security, compliance, and governance requirements, including standards such as NIST, GDPR, and SOX where applicable.
• Stay current on emerging technologies and contribute ideas that improve products, platforms, and engineering practices.
• Master’s degree in Computer Science or a STEM field.
• Relevant working experience in software engineering, data engineering, or related technical roles.
• Must have hands-on experience with Lambda, S3, API Gateway, ECS/EKS, IAM, CloudWatch, Step Functions.
• Experience with backend development using technologies such as Python, Java, and related frameworks.
• Experience designing or supporting data pipelines, ETL/ELT processes, and integrations.
• Familiarity with CI/CD, automated testing, containerization, and cloud-native tools such as Git, Docker, Kubernetes, Gradle, or Maven.
• Understanding of secure engineering practices and compliance considerations in enterprise environments.
• Experience with AI/ML deployment, integration, or monitoring.
• Experience with API orchestration, MCP-based integrations, or connected system architectures.
• Knowledge of technical data domains and enterprise data architecture.
• Ability to work effectively across teams, communicate clearly, and adapt to changing priorities.

We are an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status, or any other characteristic protected by law. We are committed to creating an inclusive environment where everyone is respected, valued, and able to contribute fully.