DevOps

Complexio; Warszawa; On-site; PLN 180,000 - 280,000; Full time

Job summary

Complexio seeks an experienced DevOps Engineer to design and operate the platform for deploying, managing, and optimizing our distributed AI-driven systems across on-premises, AWS, Azure, Google Cloud, and Kubernetes.

You will optimize data pipelines, implement CI/CD, ensure high availability and security, manage networking, and enable ML workloads on GPUs.

Qualifications

• MS/PhD in CS or related field.
• 7+ years deploying and managing cloud infrastructure (AWS, Azure, GCP).
• 3+ years working with Kubernetes environments.
• Proficient in deploying and scaling Kubernetes clusters with HA and monitoring.
• Experience with cloud-native tech, CI/CD, and containers (Docker).
• Experience integrating data from multiple sources in distributed systems.

Responsibilities

• Define and create the platform for deploying, managing, and optimizing distributed systems across on-premises and multi-cloud environments.
• Ensure infrastructure is robust, scalable, and secure to support AI solutions.
• Implement cloud-native technologies, CI/CD pipelines, and containerization to accelerate delivery; support ML workflows on GPUs.

Skills

Kubernetes

AWS

Azure

Google Cloud

CI/CD

Docker

Python/Java/Go

Scripting

Networking/Security

Documentation

Platform deployment

Education

M.Sc or Ph.D. in Computer Science

Tools

Neo4j

Vector databases

Job description

As a DevOps engineer at our AI product company, you will define and create the platform for deploying, managing, and optimizing our distributed systems across on-premises, multiple cloud environments (AWS, Azure, Google Cloud), and Kubernetes. Our system leverages multiple LLMs, Graph and Vector Databases and integrates data from multiple sources to power our AI solutions. You will ensure our infrastructure is robust, scalable, and secure, supporting the seamless delivery of our innovative products. This role requires combining cloud technologies and database management expertise, embracing the challenges of integrating AI and machine learning workflows on modern GPUs.

Requirements

• Preferred M.Sc or Ph.D. degree in Computer Science or a related field
• At least 7 years of experience deploying and managing cloud infrastructure (AWS, Azure, Google Cloud)
• At least 3 years experience working with Kubernetes environments
• Proficient in managing and scaling Kubernetes clusters, including monitoring, troubleshooting, and ensuring high availability
• Experience with cloud-native technologies, CI/CD pipelines, and containerization tools (e.g., Docker)
• Familiarity with data integration and management from multiple sources in a distributed system environment
• Proficiency in at least one programming language (Python, Java, Go), and experience with scripting for automation
• Strong understanding of network infrastructure and security principles, ensuring compliance with data protection regulations
• Excellent problem-solving and technical skills
• Experience in building platforms with custom deployment models
• Structured working approach and ability to piecemeal on long-term goals
• Ability to document and explain technical details clearly, with solid communication and collaboration skills
• Interest and experience in working on early‑stage software and solving various problems

Nice to have

• Proficient in database management, specifically with Neo4j and vector databases, including setup, scaling, and optimization for performance and reliability
• Experience deploying and running Machine Learning Solutions, including LLMs

Benefits

• Join a pioneering joint venture at the intersection of AI and industry transformation
• Work with a diverse and collaborative team of experts from various disciplines
• Opportunity for professional growth and continuous learning in a dynamic field