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Observability Internship Jobs in Washington (NOW HIRING)

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Observability Internship information

What is an observability internship?

An Observability Internship is a temporary, often entry-level position where students or recent graduates learn about and assist with monitoring, measuring, and analyzing the performance and reliability of software systems. Interns work with tools that provide visibility into applications, infrastructure, and services to help teams detect issues and improve system health. The role typically involves tasks such as setting up dashboards, analyzing logs and metrics, and helping to implement best practices for observability. This internship is valuable for those interested in DevOps, Site Reliability Engineering, or software development roles.

What types of projects and tools can I expect to work with during an observability internship?

As an Observability Intern, you'll often contribute to projects focused on monitoring, logging, and tracing the performance of software systems. You may work with popular tools such as Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), or OpenTelemetry to collect and visualize system metrics. Interns typically collaborate closely with site reliability engineers and software developers to identify bottlenecks, improve alerting, and ensure system reliability. This role provides hands-on experience with real-world infrastructure and fosters valuable problem-solving skills in a collaborative, technical environment.

What are the key skills and qualifications needed to thrive as an observability intern, and why are they important?

To thrive as an Observability Intern, you generally need foundational knowledge in computer science, familiarity with monitoring concepts, and experience with programming or scripting languages. Exposure to observability tools like Prometheus, Grafana, ELK stack, or cloud monitoring platforms, along with coursework or certifications in DevOps or cloud technologies, is often beneficial. Strong analytical thinking, problem-solving abilities, and effective communication help interns collaborate with engineering teams and interpret complex data. These skills enable interns to contribute to system reliability by identifying, diagnosing, and resolving performance issues efficiently.

What is the difference between Observability Internship vs Monitoring Internship?

AspectObservability InternshipMonitoring Internship
FocusBroad system insights, including logs, metrics, tracesReal-time system health and alerting
SkillsData analysis, debugging, understanding of distributed systemsAlert configuration, basic system metrics
Work EnvironmentDevOps, SRE teams, cloud environmentsOperations, system administration teams
CertificationsKnowledge of monitoring tools (Prometheus, Grafana), scriptingBasic monitoring tools, scripting skills

While both internships involve system health, an Observability Internship covers a broader set of tools and concepts like logs, traces, and metrics for comprehensive system understanding. Monitoring internships focus more on real-time alerts and system uptime. Understanding these differences helps candidates choose the right role aligned with their skills and career goals.

What are the most commonly searched types of Observability jobs in Washington?

The most popular types of Observability jobs in Washington are:

What are popular job titles related to Observability Internship jobs in Washington?

For Observability Internship jobs in Washington, the most frequently searched job titles are:

Director, Enterprise Research & Automation Services

Cooperative Education

Fairfax, VA โ€ข On-site

$164 - $200/hr

Other

Posted 14 days ago


Key responsibilities

  • Oversee the engineering, optimization, and scaling of the Mason Research, Intelligence, Data, and Automation Systems platform.

  • Lead the institutional automation lifecycle by designing and deploying robotic process automation, intelligent workflows, and system orchestration models.

  • Manage the research technology innovation pipeline, including evaluating emerging technologies and coordinating rapid prototyping efforts.


Job description

Department: Information TechnologyServices

Classification: Administrative Faculty

Job Category:Administrative or Professional Faculty

Job Type:Full-Time

Work Schedule:Full-time (1.0 FTE, 40 hrs/wk)

Location: Fairfax, VA

Workplace Type:On Site Required

Sponsorship Eligibility:Not eligible for visa sponsorship

Salary: Up to $182,000 annually; commensurate with education and experience

Criminal Background Check:Yes

About the Department:

The Chief Technology Officer (CTO) department drives the universityโ€™s digital modernization, technical strategy, and institutional agility through four foundational pillars: Enterprise Infrastructure, Applications, Architecture, and Research. Operating centrally within Information Technology Services (ITS), the Research pillar identifies, prototypes, evaluates, and scales cutting-edge computing environments, automated workflows, and advanced intelligence applications. The unit focuses on shifting manual paradigms into optimized digital patterns, deploying high-performance systems, and ensuring emerging platforms are safely and effectively integrated into the fabric of the university to support institutional strategy.

About the Position:

The Director, Enterprise Research & Automation Services provides strategic and technical leadership over the universityโ€™s institutional research and automation systems, advanced research pipelines, and enterprise automation strategies. This position oversees the engineering, optimization, and scaling of the Mason Research, Intelligence, Data, and Automation Systems platform, as well as enterprise-wide workflow automation initiatives. The Director manages a dedicated team of professional staff and student developers to run rapid-prototyping initiatives, eliminate manual operational friction, and support advanced research computingโ€”all while operating in strict compliance with cybersecurity, data privacy, and technology governance frameworks established by the Chief Information Officer's (CIOโ€™s) office.

Responsibilities:

Advanced Research & Automation Platform Engineering Leadership:

  • Serve as the focal point for Central Research Services to the Office of Research and Compute, and the Distributed GMU Research communityโ€”supporting GMU Research Council and stakeholder forums/working groups, etc.;
  • Direct the architectural scaling, maintenance, and technical execution of the Mason Research, Intelligence, Data, and Automation Systems platform;
  • Oversee the aggregation and indexing of complex institutional datasets into unified information pipelines, enabling real-time predictive analytics and executive visibility dashboards;
  • Enforce rigid data synchronization protocols across the platform to ensure a single source of truth (SSOT) and eliminate data fragmentation across administrative systems; and
  • Accelerate the systemic elimination of manual operational overhead across all academic, research, and administrative units through active partnership and exploration engagements of the George Mason University business and research needs.

Enterprise Automation Strategy & Process Optimization:

  • Lead the institutional automation lifecycle by identifying, designing, and deploying modern robotic process automation (RPA), intelligent workflows, functional apps, and system orchestration models across academic and operational units, intentionally converting slow, legacy department habits into high-velocity digital workflows while maintaining a centralized automation registry to minimize institutional technical debt;
  • Partner with university stakeholders to systematically review high-friction, manual workflows and transition them into high-velocity, automated digital processes;
  • Manage the automation registry to maximize the reuse of software agents and minimize technical debt;
  • Define, track, and document the financial and operational return on investment (ROI) for all research and automation deployments; and
  • Build and maintain executive observability dashboards that quantify exact administrative hours reclaimed, error rates eliminated, and compute economics optimized, providing direct visibility to ITS executive leadership.

Research Technology Innovation & Prototyping Pipeline:

  • Manage the dedicated Research, AI, and advanced computing lane in coordination with academic units and university research stakeholders;
  • Establish a structured methodology for evaluating emerging technologies, high-performance computing (HPC) workflows, and advanced digital capabilities;
  • Orchestrate a "fail small, learn big" pipeline using rapid prototyping and proofs-of-concept, directly utilizing student internship pipeline to build and test initial capabilities; and
  • Coordinate computational research support, HPC workflows, RAG models over licensed corpora, and open-science tools to secure and accelerate the university's R1 research preeminence.

Cross-Functional Integration & Compliance Operations:

  • Collaborate daily with the Applications, Architecture, and Enterprise Infrastructure pillars within the CTO department to ensure all automation and intelligence platforms scale smoothly onto core infrastructure networks, ensuring seamless platform convergence, and eliminating parallel development silos;
  • Maintain strict operational alignment with the CIOโ€™s area, ensuring that all deployed research tools, automated bots, and MIDAS projects fully comply with established university security policies, data privacy protocols (e.g., FERPA), and institutional risk frameworks; and
  • Ensure that every automated script, data ingestion pathway, software bot, and intelligence engine operates in strict compliance with the cybersecurity policies, data privacy baselines (including FERPA), and overarching governance frameworks established by the CIOโ€™s office.

Required Qualifications:

  • Bachelorโ€™s degree in related field, or equivalent combination of education and experience;
  • Significant experience (typically 6-9 years) of progressive technical leadership in automation engineering, systems development, data intelligence, or research computing environments;
  • Knowledge of enterprise automation frameworks, robotic process automation (RPA) tools, and machine learning/intelligence platform components;
  • Knowledge of advanced data integration architectures, cloud-hybrid platforms, and API-driven data pipelining methods;
  • Skill in managing complex technology portfolios, directing rapid prototyping operations, and leading full-lifecycle software or systems automation projects;
  • Leadership skillsโ€”including the ability to supervise technical engineering staff, assigning sprints, conducting code reviews, and evaluating production performance metrics;
  • Ability to translate ambiguous, high-friction administrative and academic processes into clear, structured, and logical automated workflows; and
  • Ability to work effectively across distinct IT divisionsโ€”including infrastructure, systems engineering, and architecture teamsโ€”to align deployment configurations.

Preferred Qualifications:

  • Masterโ€™s degree in related field;
  • Professional certifications in Automation Engineering, Agile/Scrum Project Management (e.g., PMP, PMI-ACP), or Enterprise Architecture are highly desirable. CRA (Certified Research Administrator), CDPSE (Certified Data Privacy Solutions Engineer), AWS Certified Solutions Architect;
  • Extensive experience (typically 10+ years) leading enterprise-level automation strategies, managing large-scale intelligence architectures, and supervising cross-functional software or infrastructure development teams within a complex, research-intensive enterprise;
  • Knowledge of R1 research institution technology demands, academic computing environments, and specialized research datasets;
  • Knowledge of enterprise data governance strategies, security baseline standards, and higher education privacy regulations (such as FERPA);
  • Skill in utilizing TeamDynamix or similar enterprise ITSM platforms to track, monitor, and prioritize technical automation queues; and
  • Ability to coach and mentor early-career developers and student interns within a fast-paced, high-focus performance culture.

Posting Open Date: August 19, 2026

Posting Close Date: September 2, 2026

Open Until Filled:No

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