2

Part Time Azure Ai Jobs (NOW HIRING)

AI Solutions Architect

Reston, VA · On-site

$140K - $203K/yr

Telework Type: Part-Time Telework * Work Location: Reston, VA, Various Work Locations USA * Salary ... Hands-on experience with cloud platforms (preferably Microsoft Azure) and cloud-native design.

AI Solutions Architect

Reston, VA · On-site +1

$140K - $203K/yr

Telework Type: Part-Time Telework * Work Location: Reston, VA, Various Work Locations USA * Salary ... Hands-on experience with cloud platforms (preferably Microsoft Azure) and cloud-native design.

AI/ML Engineer, Senior

Dayton, OH · On-site +1

$99K - $225K/yr

... such as AWS, Azure, and GCP * Experience with automated testing tools and model evaluation ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Start: Future projects in late 2026 or 2027 (not an immediate job opening) Type: Part-time ... Experience with cloud platforms (AWS, Azure, GCP) in QE/AI context. * Exposure to self-healing test ...

Start: Future projects in late 2026 or 2027 (not an immediate job opening) Type: Part-time ... Experience with cloud platforms (AWS, Azure, GCP) in QE/AI context. * Exposure to self-healing test ...

AI/ML Engineer

Arlington, VA · On-site

$77K - $176K/yr

... Azure * 2+ years of experience deploying and integrating production-grade ML models using tools ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

$26/hr

This is a part-time internship position for our Fall Rotation, from September 8, 2025 through ... Knowledge of AWS/AZURE cloud, Full Stack Development * Knowledge of Python programming, UNIX, Web ...

Showing results 41-60

Part Time Azure Ai information

See salary details

$11

$58

$79

How much do part time azure ai jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for part time azure ai in the United States is $58.40, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $65.62 per hour, depending on experience, location, and employer.

What is the difference between Part Time Azure Ai vs Part Time Data Analyst?

AspectPart Time Azure AiPart Time Data Analyst
Required CredentialsAzure certifications, basic programming skillsData analysis certifications, SQL, Excel skills
Work EnvironmentCloud platforms, tech teams, remote or onsiteBusiness environments, reporting teams, remote or onsite
Industry UsageTech, cloud services, AI developmentFinance, marketing, healthcare, business intelligence
Common Search IntentAzure AI projects, cloud AI rolesData analysis tasks, reporting, insights

Part Time Azure Ai professionals focus on developing and managing AI solutions using Azure cloud services, requiring cloud certifications and programming skills. In contrast, Part Time Data Analysts interpret data to generate reports and insights, often needing data analysis certifications and proficiency in SQL and Excel. While both roles may work remotely and in similar industries, their core responsibilities and skill sets differ significantly.

More about Part Time Azure Ai jobs

What are the most commonly searched types of Azure Ai jobs?

The most popular types of Azure Ai jobs are:

What states have the most Part Time Azure Ai jobs?

States with the most job openings for Part Time Azure Ai jobs include:

Infographic showing various Part Time Azure Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $121,476 per year, or $58.4 per hour.

Senior Staff DevOps Engineer - Data Discovery & AI Governance

OneTrust

Atlanta, GA • On-site

$125K - $160K/yr

Part-time

Posted 19 days ago


Job description

The Mission

OneTrust's mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn't slow teams down-it should accelerate what's possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI-Ready Governance Platform, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society.

The Challenge

We are hiring a Senior Staff DevOps Engineer to join our Detect & Discover (D&D) team. This team owns three product lines - Data Discovery, Privacy Automation, and AI Governance - serving thousands of enterprise customers across multi-cloud and on-premises environments.

In this role, you will lead the infrastructure strategy for our Kubernetes-based on-premises platform and cloud deployments. This includes architecting automated worker node deployments for Azure Marketplace, AWS Marketplace, and GCP; driving container-hardening initiatives to systematically eliminate CVEs; and ensuring the reliability, scalability, and security of our distributed scanning and classification platform. You will act as a technical leader, mentoring engineers and collaborating closely with product security, engineering squads, and customer-facing teams.

Your Mission
  • Kubernetes Platform Architecture: Architect and maintain production-grade Kubernetes platforms across cloud (AKS, EKS, GKE) and on-premises (K3s, microk8s) environments. Own the full lifecycle - cluster provisioning, upgrades, node pool management, and disaster recovery.
  • Deployment Automation & Marketplace Publishing: Develop and maintain automation using Helm, ARM templates, BICEP, Terraform, and CloudFormation to streamline worker node provisioning on Azure Marketplace, AWS Marketplace, and Reduce customer setup complexity so clients don't need advanced Kubernetes expertise on-site.
  • Container Hardening & Vulnerability Management: Lead our container-hardening program by adopting secure base images for distributed components including Kafka, PostgreSQL, Elasticsearch, Temporal and Vault. Own the systematic reduction of CVEs flagged by Vulnerability Scanners.
  • CI/CD & Release Engineering: Maintain and improve CI/CD pipelines ensuring zero-downtime deployments, automated rollbacks, and full auditability. Drive GitOps practices, Improve DevEx and infrastructure-as-code across the team.
  • Observability & Platform Reliability: Design monitoring, alerting, diagnostics, and self-healing capabilities using Datadog, Loki, Promtail. Ensure the platform is optimized for performance, logarithmic cost growth, and high-throughput scaling across thousands of tenant environments.
  • Incident Response & Production Support: Lead incident investigations, root cause analysis, and long-term remediation for production service interruptions. Participate in on-call rotation and drive systemic fixes to prevent recurrence.
  • Mentorship & Technical Leadership: Mentor engineers, drive DevOps best practices across teams, and raise the technical bar for infrastructure engineering quality.
You Are
  • A hands-on technical leader with strong analytical and problem-solving skills and a passion for high-quality infrastructure engineering.
  • Technically curious and self-motivated, able to self-teach new technologies and prioritize complex tasks in a fast-paced environment.
  • A collaborative partner who works seamlessly with security teams, software developers, and product managers to drive alignment on infrastructure standards.
  • Someone who thrives in ambiguous environments, takes ownership of complex technical challenges, and influences across teams without direct authority.
  • An encouraging mentor who enjoys upskilling engineers and continuously improving reliability, automation, and customer experience.
Your Experience Includes
  • Education: Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • Experience: 8+ years in DevOps, SRE, or Platform Engineering roles.
  • Container Orchestration: Expert knowledge of Kubernetes, Helm, Linux, Docker, and networking
  • Multi-Cloud Platforms: Strong working knowledge of Azure, AWS, and GCP, with specific depth in at least one.
  • Automation & Scripting: Proficiency in Go and/or Python, plus Bash/Shell scripting for infrastructure automation and integrations.
  • CI/CD & GitOps: Deep understanding of CI/CD pipelines (GitLab or similar), GitOps workflows, and infrastructure-as-code methodologies.
  • Databases & Messaging: Experience with PostgreSQL, Elasticsearch, and distributed messaging systems (Apache Kafka, NATS).
  • Security & Compliance: Experience with security scanning, container image hardening, and vulnerability remediation in enterprise environments.
  • Production Operations: Experience supporting enterprise production environments and handling customer escalations.
  • Methodologies: Prior experience working in Agile/Scrum enterprise software development.
  • Communication: Excellent verbal and written communication and technical leadership skills.
Extra Awesome
  • Experience building and publishing B2B enterprise software on Azure Marketplace, AWS Marketplace, or GCP Marketplace.
  • Proven experience with Chainguard or other minimal, hardened container distributions for software supply chain security.
  • Experience with on-premises enterprise software deployments (K3s, microk8s, airgapped environments).
  • Familiarity with Temporal workflow orchestration or similar durable execution frameworks.
  • Prior exposure to MLOps methodologies, including model versioning, pipeline auditability, and AI asset discovery.
  • Experience with service meshes, Kubernetes operators, and AI-assisted operations.