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Gitlab Ci Pass Variables Between Jobs (NOW HIRING)

Genesis10

Quality Engineer

Charlotte, NC · On-site

$70K - $90K/yr

... Jenkins/GitLab CI) with gating policies, test dashboards, and quality thresholds • Author ... variables/secrets, and test parallelization • Proven capability with SQL and at least one NoSQL ...

Hermeus

DevOps Engineer - Flight Software

Atlanta, GA

$50.75 - $69.50/hr

Design, implement, and maintain scalable Gitlab CI/CD pipelines to support flight software build ... Ability to move quickly between infrastructure design, hands-on implementation, debugging, and ...

Hermeus

DevOps Engineer - Flight Software

Los Angeles, CA

$56.75 - $77.75/hr

Design, implement, and maintain scalable Gitlab CI/CD pipelines to support flight software build ... Ability to move quickly between infrastructure design, hands-on implementation, debugging, and ...

Hermeus

DevOps Engineer - Flight Software

Atlanta, GA · On-site

$177K - $205K/yr

Design, implement, and maintain scalable Gitlab CI/CD pipelines to support flight software build ... Ability to move quickly between infrastructure design, hands-on implementation, debugging, and ...

ECS

CI/CD Pipeline Engineer

Falls Church, VA · On-site

... between Combatant Commands, Joint Staff directorates, Senior Executive Service leaders, and ... using GitLab CI, Argo Workflows, Kubernetes, container scanning platforms, software composition ...

Hermeus

DevOps Engineer - Flight Software

Atlanta, GA

$177K - $205K/yr

Design, implement, and maintain scalable Gitlab CI/CD pipelines to support flight software build ... Ability to move quickly between infrastructure design, hands-on implementation, debugging, and ...

Hermeus

DevOps Engineer - Flight Software

Atlanta, GA · On-site

$177K - $205K/yr

Design, implement, and maintain scalable Gitlab CI/CD pipelines to support flight software build ... Ability to move quickly between infrastructure design, hands-on implementation, debugging, and ...

Bluestone Logic

Test Engineer - Senior

Washington, DC · On-site

Lead end-to-end system validation efforts, ensuring all SXXI updates pass UAT, regression, and ... GitLab CI/CD pipelines. * Develop automated API test cases ensuring interoperability between SXXI ...

Cordova

DevOps Engineer

Omaha, NE · On-site

$50.50 - $69/hr

Your goal will be to bridge the gap between development and operations, enabling our teams to ... GitLab CI/CD) and automation scripts Strong problem-solving skills and attention to detail ...

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Gitlab Ci Pass Variables Between information

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$104K

$144K

How much do gitlab ci pass variables between jobs pay per year?

As of Jun 10, 2026, the average yearly pay for gitlab ci pass variables between in the United States is $104,014.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $124,000.00 per year, depending on experience, location, and employer.

How do you pass variables between jobs in GitLab CI?

In GitLab CI, you can pass variables between jobs by using 'artifacts' or by defining variables in the 'job' or 'pipeline' scope. Artifacts allow you to store files or outputs from one job and make them available to subsequent jobs in later stages. For simple key-value pairs, you can write variables to a file in one job, save the file as an artifact, and then read the file in the next job. Additionally, you can use 'needs' or 'dependencies' to control job execution and variable sharing. This approach helps maintain flexibility and modularity in your CI/CD pipelines.

What are some best practices for securely passing variables between GitLab CI/CD pipeline stages?

When passing variables between GitLab CI/CD pipeline stages, it's important to use GitLab's built-in CI/CD variables and artifacts features. Sensitive values, such as API keys or passwords, should always be stored as protected or masked variables in GitLab's CI/CD settings to prevent exposure in logs. Additionally, avoid echoing secrets in scripts, and use the 'dependencies' and 'artifacts' keywords to pass non-sensitive data between jobs. This approach ensures your pipelines remain secure and maintainable while allowing for flexible data transfer between stages.

What are the key skills and qualifications needed to thrive as a DevOps Engineer working with GitLab CI, and why are they important?

To thrive as a DevOps Engineer specializing in GitLab CI, you need strong knowledge of CI/CD concepts, scripting languages (such as Bash or Python), and experience with version control systems like Git. Proficiency in using GitLab CI/CD pipelines, YAML configuration, environment variables, and integrating with tools like Docker or Kubernetes is essential. Effective problem-solving, attention to detail, and strong collaboration skills help you manage complex build and deployment processes efficiently. These skills are crucial for automating software delivery, ensuring reliable deployments, and fostering continuous integration and collaboration across development teams.

What is the difference between Gitlab Ci Pass Variables Between and Gitlab CI/CD Pipeline Engineer?

FeatureGitlab Ci Pass Variables BetweenGitlab CI/CD Pipeline Engineer
Role FocusManaging CI/CD variables and their transfer between jobsDesigning, implementing, and maintaining CI/CD pipelines
Skills RequiredUnderstanding of GitLab CI/CD variables, scriptingDeep knowledge of pipeline architecture, scripting, automation
Work EnvironmentDevOps teams, CI/CD pipeline setupDevOps teams, pipeline development and optimization

Gitlab Ci Pass Variables Between is a specific task within CI/CD workflows, focusing on passing variables between jobs. In contrast, a Gitlab CI/CD Pipeline Engineer designs and manages entire pipelines. While both roles require knowledge of GitLab CI/CD, the former is more about executing specific tasks, and the latter involves comprehensive pipeline development and maintenance.

What job categories do people searching Gitlab Ci Pass Variables Between jobs look for? The top searched job categories for Gitlab Ci Pass Variables Between jobs are:
Infographic showing various Gitlab Ci Pass Variables Between job openings in the United States as of June 2026, with employment types broken down into 17% As Needed, 37% Full Time, 33% Part Time, 3% Contract, and 10% Nights. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $104,014 per year, or $50 per hour.
Software Engineer - Agentic AI Platform

Software Engineer - Agentic AI Platform

Avispa Technology

San Francisco, CA • On-site

$75 - $100/hr

Full-time

Medical, Dental, Vision, Life, Retirement

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Software Engineer - Agentic AI Platform

  • Hourly pay: $75-$100/hr (Depends on years of experience)
  • Worksite: Leading audio, video, and voice technologies company (Remote - Open for candidates located in the United States)
  • W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
  • 40 hours/week, 6 Month Assignment

A leading video, audio, and voice technologies company is seeking a Software Engineer - Agentic AI Platform to build and extend a centralized Agentic AI framework that enables secure, governed, and cost-aware AI agents across enterprise GitLab workflows. This role will focus on developing AWS-based agent orchestration services, integrating AI capabilities into CI/CD pipelines, implementing security and observability controls, and delivering scalable platform services that enable engineering teams to adopt AI without rearchitecting their existing

Software Engineer - Agentic AI Platform Responsibilities:

  • Design, develop, and maintain AI agent orchestration services using AWS Lambda, SQS, EventBridge, API Gateway, and Amazon Bedrock Agents; build routing logic, event-driven workflows, and scalable agent execution frameworks.
  • Integrate AI agents into GitLab CI/CD pipelines by developing reusable pipeline patterns, automating agent execution stages, consuming repository and testing context, generating artifacts, and enforcing pass/fail quality gates.
  • Build and maintain Bedrock Action Groups, Knowledge Bases, and retrieval systems leveraging AWS Lambda, OpenSearch, S3, and enterprise data sources to enable contextual and scalable AI decision-making.
  • Implement security, governance, and operational controls, including Bedrock Guardrails, IAM policies, secrets management, input/output validation, audit logging, token usage controls, model routing strategies, semantic caching, and cost optimization mechanisms.
  • Develop observability, monitoring, and reporting solutions using CloudWatch and related AWS services; create dashboards, tracing, logging, compliance reporting, and operational insights while partnering with engineering teams to deliver reliable AI platform capabilities.

Software Engineer - Agentic AI Platform Qualifications:

  • 3-7 years of professional software engineering experience developing cloud-native applications and distributed systems.
  • A bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline is preferred.
  • Strong Python development experience, including AWS SDK (Boto3) and production-grade AWS Lambda development.
  • Hands-on experience with AWS services, including Lambda, API Gateway, SQS, EventBridge, IAM, Secrets Manager, and CloudWatch.
  • Experience working with Amazon Bedrock, including Agents, Action Groups, Knowledge Bases, and Guardrails.
  • Experience integrating with LLM platforms such as Amazon Bedrock, OpenAI, Anthropic, or similar AI services.
  • Strong understanding of GitLab CI/CD pipelines, automation workflows, and software delivery practices.
  • Experience designing secure cloud solutions with knowledge of IAM, secrets management, least-privilege access controls, input validation, and AI security considerations such as prompt injection and data protection.
  • Experience implementing observability solutions, including structured logging, monitoring, tracing, and production troubleshooting.
  • Experience developing event-driven architectures, APIs, and microservices is preferred.
  • Experience with OpenSearch, vector search, embeddings, retrieval-augmented generation (RAG), or semantic search technologies is preferred.
  • Experience with FinOps, TokenOps, model routing, semantic caching, cost attribution, or AI operational governance is preferred.
  • Experience building internal developer platforms, engineering enablement tools, or shared infrastructure services is preferred.
  • Familiarity with agent frameworks and multi-agent architectures is preferred.