Staff Software Engineer, Infrastructure (Cloud)

AeroVect; Poland; On-site; PLN 220,000 - 360,000; Full time

Job summary

AeroVect is seeking a Staff Software Engineer, Infrastructure (Cloud) to own data infrastructure powering its autonomous driving platform. You will design scalable data pipelines moving operational data from on-prem to the cloud and build robust cloud services on AWS.

You will implement infrastructure-as-code, manage CI/CD pipelines, and collaborate with autonomy and systems engineers to deliver reliable systems for large-scale deployments worldwide.

Qualifications

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• 7+ years of experience building cloud infrastructure and data systems for large-scale distributed systems.
• Strong proficiency in Python with a focus on data pipeline development and automation.
• Hands-on experience with Kafka, Kubernetes, and gRPC for building scalable, high-throughput data systems.
• Deep expertise with AWS cloud services including compute, storage, and data processing.
• Experience with CI/CD platforms (Jenkins, GitHub Actions, CircleCI).
• Proficiency with containerization and orchestration (Docker, Kubernetes).
• Experience automating deployments with Terraform or CloudFormation.
• Familiarity with Git-based workflows, code review processes, and collaborative software development.

Responsibilities

• Design, build, and maintain scalable data pipelines that move operational data from on-prem systems into cloud infrastructure
• Architect and manage cloud-based infrastructure (AWS) for scalable computation, data processing, and system telemetry
• Integrate on-prem and cloud data flows into a cohesive, reliable data architecture
• Build and maintain CI/CD pipelines to enable rapid, reliable software delivery and validation across simulation and real-world testing environments
• Implement and manage infrastructure-as-code (Terraform, CloudFormation) for consistent, automated provisioning
• Develop internal services and automation tools to streamline data ingestion, processing, and observability
• Establish and enforce best practices for data reliability, pipeline observability, and system security
• Drive root-cause analysis for data infrastructure and pipeline issues; design long-term solutions to improve system resilience
• Collaborate with autonomy and systems engineers to define scalable data interfaces and cloud deployment strategies

Skills

Python

Data pipelines

Cloud infrastructure

Kafka

Kubernetes

gRPC

AWS

CI/CD

Docker

Terraform

CloudFormation

Git workflows

Education

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field

Tools

Terraform

CloudFormation

Docker

Jenkins

GitHub Actions

CircleCI

Job description

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

As a Staff Software Engineer, Infrastructure (Cloud), you will own the data infrastructure and cloud systems that power AeroVect's autonomous driving platform. You'll design and scale the pipelines that move operational data from real-world deployments into the systems that drive development, testing, and continuous improvement — ensuring reliability and performance

This is a highly impactful role at the intersection of cloud infrastructure and data engineering. You'll have real ownership — designing systems from the ground up, not inheriting a finished stack. The opportunity to grow into a technical leadership role is real as the team scales.

You Will

• Design, build, and maintain scalable data pipelines that move operational data from on-prem systems into cloud infrastructure
• Architect and manage cloud-based infrastructure (AWS) for scalable computation, data processing, and system telemetry
• Integrate on-prem and cloud data flows into a cohesive, reliable data architecture
• Build and maintain CI/CD pipelines to enable rapid, reliable software delivery and validation across simulation and real-world testing environments
• Implement and manage infrastructure-as-code (Terraform, CloudFormation) for consistent, automated provisioning
• Develop internal services and automation tools to streamline data ingestion, processing, and observability
• Establish and enforce best practices for data reliability, pipeline observability, and system security
• Drive root-cause analysis for data infrastructure and pipeline issues; design long-term solutions to improve system resilience
• Collaborate with autonomy and systems engineers to define scalable data interfaces and cloud deployment strategies

You Have

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field
• 7+ years of experience building cloud infrastructure and data systems for large-scale distributed systems
• Strong proficiency in Python with a focus on data pipeline development and automation
• Hands-on experience with Kafka, Kubernetes, and gRPC for building scalable, high-throughput data systems
• Deep expertise with AWS cloud services including compute, storage, and data processing
• Experience with CI/CD platforms (Jenkins, GitHub Actions, CircleCI)
• Proficiency with containerization and orchestration (Docker, Kubernetes)
• Experience automating deployments with Terraform or CloudFormation
• Familiarity with Git-based workflows, code review processes, and collaborative software development

We Prefer

• Experience integrating on-prem and cloud data flows in a hybrid infrastructure environment
• Background in data engineering for robotics, autonomous systems, or real‑time operational data
• Knowledge of monitoring, logging, and alerting tools such as Prometheus, Grafana, or the ELK Stack
• Familiarity with networking, security, and distributed system performance optimization
• Experience supporting safety-critical, real‑time, or high-availability systems