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Junior Aiops Engineer Jobs (NOW HIRING)

Redfish Recruiting

Contributions to AIops/MLOps platforms (MLflow, Kubeflow, Vertex AI) and CI/CD for ML workflows ... Mentor senior/junior engineers in AI/ML best practices, distributed systems, experimentation, and ...

Flexential

Sr Platform Engineer-1

Denver, CO · On-site

... junior engineers and managing critical platform subsystems. Responsibilities : • Design, develop ... ArgoCD or Flux preferred • AIOps / Observability Engineering - 2+ years, Alertmanager rule ...

New

Spatial Front, Inc.

Senior Software Developer

Bethesda, MD · Hybrid

$90K - $130K/yr

... junior developers, and collaborate closely with cross-functional stakeholders to deliver high ... Certified Engineer - Ansible Automation, or equivalent) * Certification in AIOps or Data/ML ...

Spatial Front, Inc.

Senior Software Developer

Bethesda, MD · On-site

$90K - $130K/yr

... junior developers, and collaborate closely with cross-functional stakeholders to deliver high ... Certified Engineer - Ansible Automation, or equivalent) * Certification in AIOps or Data/ML ...

Adidev Technologies Inc

DevOpsEngineer

Washington, DC · On-site

$59.50 - $81.50/hr

... junior engineers and contribute to architectural decisions. - Lead incident response and perform ... AIOps or predictive automation. - Leadership or mentoring experience. What Youll Gain ...

Adidev Technologies

DevOpsEngineer

Washington, DC · On-site

$59.50 - $81.50/hr

M entor junior engineers and contribute to architectural decisions. * L ead incident response and ... E xperience with AIOps or predictive automation. * L eadership or mentoring experience. What You'll ...

Sovrn

Senior Cloud Engineer

Boulder, CO

$57.75 - $77.25/hr

Implement AIOps solutions for automated anomaly detection; define standards for responsible AI use ... help junior engineers develop their technical writing skills. * Stay current with emerging ...

Sovrn

Senior Cloud Engineer

Boulder, CO · On-site

$57.75 - $77.25/hr

Implement AIOps solutions for automated anomaly detection; define standards for responsible AI use ... help junior engineers develop their technical writing skills. * Stay current with emerging ...

Guardianlife

Lead AI Engineer

Holmdel, NJ · On-site +1

$118K - $195K/yr

... AIOps * Familiarity with Containerization and Orchestration technologies, Sagemaker * Strong ... Mentor junior team members and foster a culture of technical excellence You will: * Be part of a ...

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All JobsJunior Aiops Engineer Jobs

Junior Aiops Engineer information

See salary details

$33.5K

$71.8K

$109.5K

How much do junior aiops engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for junior aiops engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.

What are Junior AIOps Engineers?

Junior AIOps Engineers are entry-level professionals who assist in implementing and maintaining artificial intelligence for IT operations (AIOps) solutions. They help analyze IT data, automate routine tasks, and detect incidents using machine learning and analytics tools. Their role typically involves monitoring systems, identifying anomalies, and supporting the integration of AI-driven tools to improve IT efficiency and responsiveness. Junior AIOps Engineers often work under the guidance of senior engineers while gaining experience with modern IT infrastructure and AI technologies.

What is the difference between Junior Aiops Engineer vs Data Analyst?

AspectJunior Aiops EngineerData Analyst
Required SkillsBasic knowledge of AI operations, scripting, cloud platformsData interpretation, SQL, Excel, statistical analysis
CertificationsEntry-level certifications in cloud or AI toolsData analysis or visualization certifications
Work EnvironmentIT operations, cloud environments, AI toolsBusiness intelligence, data reporting teams
Industry UsageTech, cloud service providers, AI companiesFinance, marketing, healthcare, research

The Junior Aiops Engineer focuses on maintaining AI and cloud operations, requiring scripting and cloud skills, while Data Analysts interpret data to inform business decisions. Both roles involve data handling but serve different functions within organizations.

What are the key skills and qualifications needed to thrive as a Junior AIOps Engineer, and why are they important?

To thrive as a Junior AIOps Engineer, you need foundational knowledge of IT operations, scripting languages (such as Python or Bash), and a relevant degree in computer science or related fields. Familiarity with monitoring tools (like Nagios, Prometheus), cloud platforms, and basic machine learning concepts is typically expected, along with certifications like AWS Certified Cloud Practitioner or Google Cloud Associate. Strong problem-solving abilities, effective communication, and a proactive learning attitude set candidates apart in this evolving field. These skills enable efficient incident response, automation of routine tasks, and successful collaboration within IT teams to ensure system reliability and innovation.

What are some typical challenges faced by Junior AIOps Engineers when working with large-scale IT infrastructures?

Junior AIOps Engineers often encounter challenges related to managing and interpreting vast amounts of IT operations data from diverse sources. Adapting to various monitoring tools, troubleshooting incidents efficiently, and learning how to automate repetitive tasks using machine learning can be demanding at first. Collaboration with cross-functional teams—such as DevOps, IT support, and data engineers—is also essential, requiring good communication skills. Over time, mastering these areas leads to greater autonomy and opportunities for advancement within IT operations and AIOps roles.
More about Junior Aiops Engineer jobs
What cities are hiring for Junior Aiops Engineer jobs? Cities with the most Junior Aiops Engineer job openings:
What are the most commonly searched types of Aiops Engineer jobs? The most popular types of Aiops Engineer jobs are:
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What job categories do people searching Junior Aiops Engineer jobs look for? The top searched job categories for Junior Aiops Engineer jobs are:
Junior Aiops Engineer jobs near you
Infographic showing various Junior Aiops Engineer job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $71,799 per year, or $34.5 per hour.

Principal Engineer

Redfish Recruiting

On-site, Remote

Full-time

PTO

Posted 3 days ago

Job description

Job description
Drive the end-to-end technical strategy, architecture, and productionization of ProveAI's machine learning systems, large language model (LLM) capabilities, and AI infrastructure. Own how models, evaluation pipelines, data workflows, and observability components are designed, deployed, monitored, and continuously improved to meet reliability, quality, safety, and cost goals. Provide deep AI/ML expertise and leadership across engineering teams, guiding model integration, AI/ML platform decisions, and scalable distributed systems that support enterprise-grade GenAI workloads.
Job requirements
  • 10+ years of software engineering experience with significant recent hands-on AI/ML/AI development.
  • Bachelor's degree in CS or related field.
  • Deep technical expertise in machine learning, LLMs, transformers, and modern AI frameworks (PyTorch, TensorFlow, JAX, Scikit-learn).
  • Proven experience deploying production AI/ML or LLM systems at scale (not prototypes).
  • Strong programming expertise in Python; additional experience in Java, C++, or JavaScript is a plus.
  • Experience with data engineering workflows, feature stores, and scalable data pipelines.
  • Expertise with cloud platforms (AWS/GCP/Azure), containerization, orchestration (Kubernetes), and distributed systems.
  • Hands-on AI/MLOps: model deployment, monitoring, CI/CD for AI/ML, experiment tracking, and evaluation frameworks.
  • Demonstrated technical leadership managing teams of 10+ engineers and influencing cross-functional architecture.
  • Strong ability to translate ambiguous business needs into clear technical requirements and production outcomes.
  • Expertise with LLM productionization including finetuning, retrieval-augmented generation (RAG), safety/guardrails, and evaluation.
  • Experience with AI/ML flow, Kubeflow, Vertex AI, SageMaker, or similar platforms.
  • Background in model governance, drift detection, fairness/bias evaluation, and compliance.
  • Domain specialization (NLP, computer vision, recommender systems, or agentic systems).

Nice to Have:
  • Master's or PhD in Computer Science, Machine Learning, or related discipline.
  • Cloud platform expertise (AWS, GCP, Azure) with experience deploying AI/ML workloads at scale
  • Strong product mindset with ability to translate business requirements into technical solutions
  • Contributions to AIops/MLOps platforms (MLflow, Kubeflow, Vertex AI) and CI/CD for ML workflows
  • Domain expertise in specific AI application areas such as computer vision, NLP, or recommendation systems
  • Experience with model monitoring, drift detection, and model governance in production environments
  • Previous experience with AI observability and troubleshooting

Job responsibilities
  • Define and own the architecture for scalable AI/ML systems, including training, fine-tuning, inference, evaluation, and monitoring pipelines.
  • Translate ambiguous business and product requirements into robust AI/ML system designs and staged delivery plans.
  • Make strategic decisions on model selection, LLM integrations, evaluation frameworks, model gateways, guardrails, and safety mechanisms.
  • Lead design reviews, architecture forums, and technical decision-making across teams.
  • Build and deploy production-grade AI/ML/LLM models, transformers, and generative AI features-from initial concept through production rollout.
  • Establish standards for model readiness, evaluation gates, rollout/rollback, drift detection, observability, and ongoing performance management.
  • Partner with engineering teams to integrate models into distributed systems with clear SLOs, telemetry, and error-budget mechanisms.
  • Design and improve data pipelines, feature stores, and data quality/lineage workflows supporting model training and inference.
  • Develop scalable AI/MLOps/AIOps practices for automation of training, testing, deployment, and monitoring.
  • Evaluate and implement AI/ML workflow orchestration platforms (e.g., AI/MLflow, Kubeflow, Vertex AI) and CI/CD for AI/ML.
  • Own evaluation pipelines-latency, accuracy, cost, hallucination metrics, prompt versioning, and model performance insights.
  • Instrument tracing and model observability using best-practice frameworks and telemetry standards.
  • Implement guardrails and safety systems to ensure consistent, controlled behaviour of LLM-powered features.
  • Partner closely with product, engineering, and leadership to shape platform strategy and AI feature roadmap.
  • Provide trade-off analyses that incorporate model performance, security, compliance, scalability, and long-term maintainability.
  • Write clear technical documents, proposals, and mechanism-based recommendations to guide executive decision-making.
  • Mentor senior/junior engineers in AI/ML best practices, distributed systems, experimentation, and model governance.
  • Support hiring, leveling, performance feedback, and the growth of a high-calibre engineering team.

Job benefits
  • Fully remote, work from home environment
  • Employee Share Option Plan
  • Flexible working hours
  • Paid Time-Off
  • Periodic in-person offsites globally (travel permitting)
  • Continued education support
  • Advancement opportunity

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