Key Facts

Remote From:

Full time

Junior (1-2 years)

English

Hard Skills

CI/CD Python (Programming Language) Software Engineering Kubernetes Linux Observability Containerization Application Programming Interface (API) Context Analysis AI Testing +20 more

Other Skills

•
Incident Reporting
•
Troubleshooting (Problem Solving)

Roles & Responsibilities

Strong software engineering fundamentals with proficiency in Python.
Experience building backend systems, APIs, and automation tooling in distributed Linux environments.
Practical experience with LLM systems and AI tooling, including RAG architectures, embeddings, vector search, and workflow orchestration.
Experience with CI/CD systems and cloud-native infrastructure (Kubernetes, containers, observability tooling, infrastructure automation).

Requirements:

Build AI-assisted tooling to improve engineering workflows, developer productivity, and operational efficiency across large-scale infrastructure.
Develop AI-driven CI/CD and DevOps solutions (pipeline analysis, failure classification, flaky test detection, release validation, dependency impact analysis) and improve reliability and visibility of engineering pipelines.
Design and deploy LLM-based agent systems (co-pilots, RAG/context management, internal assistants) and integrate AI with engineering systems, repositories, CI/CD platforms, documentation, observability tools, and data sources.
Deploy and maintain production-grade AI services with emphasis on observability, latency, cost, scalability, security, and secure integrations.

Virtuozzo

About Virtuozzo

Virtuozzo provides hyperconverged cloud software and services for CSPs, MSPs, ISVs and enterprises. From Infrastructure-as-a-Service and Platform-as-a-Service to Anything-as-a-Service, our mission is to make cloud easy, accessible and affordable for all. Using our production-ready OpenStack cloud platform reduces cost and improves margins for cloud service providers, and reduces cost and complexity for their customers too. Virtuozzo developed the first commercially available container virtualization technology and is an active contributor to many influential open source projects and foundations, including Linux kernel, OpenVZ, Docker, Kubernetes, CRIU™, KVM, libvirt, QEMU, OpenStack, CNCF and OCI.

Company type: Scaleup

Founded: 2018

Company size: 201 - 500

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Job description

Junior AI Engineer
About Virtuozzo Virtuozzo is a leader in cloud infrastructure system software for AI. We offer an optimized operating system, orchestration, and management to service providers, SaaS companies, and the enterprise. Virtuozzo provides mainframe-like performance, reliability, and security while dramatically lowering overall cost and complexity.

Role Overview
At Virtuozzo, the AI Engineer focuses on applying AI to improve software engineering, DevOps, CI/CD, operational workflows, and engineering productivity across large-scale infrastructure and platform environments.

This role is centered on internal engineering effectiveness. The primary goal is to reduce operational overhead, improve reliability, accelerate delivery, and increase engineering efficiency through practical AI systems and automation.

The team may expose some capabilities as shared internal services or reusable platform components, but the core focus remains engineering operations and software delivery systems.

Key Responsibilities
Engineering Productivity

Build AI-assisted tooling for engineering workflows
Improve developer productivity and operational efficiency
Design systems that reduce repetitive manual engineering work
Support large-scale multi-component software delivery environments

CI/CD & DevOps Intelligence

Develop AI-driven solutions for:
- pipeline analysis
- failure classification
- flaky test detection
- release validation
- dependency impact analysis
- build optimization
- deployment risk analysis
Improve reliability and visibility of engineering pipelines

Operational & Engineering Automation

Build AI systems for:
- troubleshooting assistance
- incident investigation
- log analysis
- engineering knowledge retrieval
- operational recommendations
Automate engineering support and operational workflows

LLM & Agent Systems

Design and implement:
- engineering copilots
- RAG systems, context management systems
- internal engineering assistants
- workflow automation agents
Integrate AI with engineering systems, repositories, CI/CD platforms, documentation, observability tools, and operational data sources

Infrastructure & Reliability

Deploy and maintain production-grade AI services
Ensure observability, monitoring, evaluation, and operational reliability
Optimize AI systems for latency, cost, and scalability
Maintain secure and maintainable integrations

Required Qualifications
Engineering

Strong software engineering fundamentals
Strong Python skills
Experience building backend systems, APIs, and automation tooling
Experience with distributed systems and Linux environments

AI & Automation

Practical experience with LLM systems and AI tooling
Experience with:
- RAG architectures
- embeddings
- vector search
- workflow orchestration
- AI evaluation
Ability to build production systems, not just prototypes

DevOps & Infrastructure

Experience with CI/CD systems
Familiarity with:
- Kubernetes
- containers
- observability tooling
- infrastructure automation
- cloud-native environments
Understanding of operational workflows and engineering lifecycle challenges

Nice-to-Have

Experience with OpenStack ecosystems
Experience with large-scale monorepo or multi-repository environments
Experience with engineering analytics and developer productivity metrics
Familiarity with infrastructure observability and incident management systems

What Success Looks Like

Reduced engineering operational overhead
Faster issue investigation and troubleshooting
Improved CI/CD reliability and visibility
Higher engineering efficiency and delivery velocity
AI systems adopted in daily engineering workflows
Measurable reduction in repetitive manual work

What We Offer:

Flexible hours and remote work options
Competitive compensation with diffrent benefits depending on your location and type of contract
Recognition programs
Space for creativity and experimentation within the company’s goals
Supportive, engineering-driven culture with minimal bureaucracy
The chance to influence infrastructure decisions from day one
A smart, friendly team that values reliability, simplicity, and automation