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Observability Jobs in Virginia (NOW HIRING)

Senior Observability Engineer

Alexandria, VA · On-site

$111K - $153K/yr

Leidos Digital Modernization sector is seeking an experienced Senior Observability Engineer to support the delivery, enhancement, and adoption of enterprise data and analytics products used across ...

DevOps Engineer - Lead

Richmond, VA · On-site

$52.25 - $71.50/hr

Observability Tools: Proficiency in monitoring, logging, and tracing tools, including Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), Splunk, Datadog, New Relic, and cloud-native ...

DevOps engineer

Richmond, VA · On-site

$52.25 - $71.50/hr

Implement and manage full-stack observability using Datadog, ensuring seamless monitoring across infrastructure, applications, and services. * Instrument agents for on-premise, cloud, and hybrid ...

... observability, and service-level indicator frameworks supporting AI and machine learning model-serving operations across all WDP classification enclaves, ensuring enterprise-wide operational ...

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Showing results 1-20

Observability information

See Virginia salary details

$16

$60

$85

How much do observability jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for observability in Virginia is $60.01, according to ZipRecruiter salary data. Most workers in this role earn between $50.29 and $68.89 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Observability position, and why are they important?

To thrive in an Observability role, you need a strong background in monitoring, alerting, logging, and analyzing system performance, often supported by a degree in computer science or related field. Familiarity with tools such as Prometheus, Grafana, Datadog, Splunk, and experience with cloud platforms and scripting languages is crucial. Excellent problem-solving, communication, and collaboration skills help you work effectively with cross-functional engineering and operations teams. These capabilities are essential to ensure system reliability, quickly detect issues, and maintain seamless digital experiences.

What is an Observability job?

An Observability job focuses on ensuring the performance, reliability, and health of software systems by collecting, analyzing, and visualizing telemetry data such as logs, metrics, and traces. Professionals in this field work with monitoring tools, distributed tracing, and alerting systems to detect and troubleshoot issues proactively. They collaborate with engineering and operations teams to improve system visibility, reduce downtime, and enhance overall system performance.

What are the typical day-to-day responsibilities of someone in an Observability role?

In an Observability role, your daily tasks often include designing and maintaining monitoring dashboards, configuring alerts, analyzing system logs, and working closely with development and operations teams to troubleshoot issues. You'll proactively identify areas of improvement to increase system reliability, document monitoring strategies, and support incident response efforts. Collaboration is key, as you may participate in post-incident reviews and help drive architectural improvements based on the data you collect. The role is dynamic and requires a proactive approach to ensure systems stay healthy and downtime is minimized.

What are the most commonly searched types of Observability jobs in Virginia? The most popular types of Observability jobs in Virginia are:
What cities in Virginia are hiring for Observability jobs? Cities in Virginia with the most Observability job openings:
Infographic showing various Observability job openings in Virginia as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $124,828 per year, or $60 per hour.
Senior ML Observability Engineer with Security Clearance

Senior ML Observability Engineer with Security Clearance

ECS

Fairfax, VA

$103K - $142K/yr

Other

Posted 15 days ago


Job description

Job Description Everforth ECS is seeking a Senior ML Observability Engineer to work in the National Capital Region covering the Pentagon, Falls Church, and Fairfax . Please Note: This position is contingent upon contract award. The War Data Platform (WDP) is a key initiative within the U.S. Department of War's (DoW) AI-First strategy introduced in early 2026. The WDP focuses on operational warfighting data and aims to accelerate the deployment of artificial intelligence (AI) on the battlefield. The WDP extends to Unclassified, Secret, and Top Secret environments, and supports collaboration between Combatant Commands, Joint Staff directorates, Senior Executive Service leaders, and operational analysts. The Senior ML Observability Engineer architects and governs the instrumentation and telemetry infrastructure needed to ensure production AI and machine learning models deployed across WDP's multi-enclave environment perform reliably and securely at mission scale. This role is essential to maintaining real-time visibility into model behavior, pipeline execution, and cross-domain access interactions in direct support of Combatant Command and Joint Staff decision-making needs. • Designs, implements, and governs observability and instrumentation architectures supporting AI and machine learning model-serving operations across Unclassified, Secret, and Top Secret enclaves within the War Data Platform (WDP) Core Integration enterprise.
• Develops semantic conventions, runtime instrumentation patterns, and telemetry pipelines that generate latency metrics, error signatures, throughput indicators, model-specific performance signals, and operational readiness measurements for deployed models and serving surfaces.
• Integrates observability capabilities into existing data pipelines, model-deployment workflows, API access patterns, and serving runtime frameworks to provide mission-relevant monitoring aligned with Combatant Command and Joint Staff decision-support needs.
• Configures and validates instrumentation using platforms such as OpenTelemetry, Prometheus, Grafana, Elastic, Splunk, Amazon CloudWatch, and service mesh telemetry components to deliver real-time visibility into model behavior, cross-domain access interactions, and pipeline execution characteristics.
• Conducts observability readiness reviews, supports test and evaluation gates, and collaborates with cybersecurity personnel to embed anomaly-detection signals aligned with Zero Trust and DoW cyber standards.
• Works with serving engineers, pipeline engineers, platform teams, and external provider integration engineers to maintain observability consistency across enclaves and resolve domain-specific telemetry constraints.
• Produces observability standards, instrumentation specifications, dashboards, alerting configurations, and performance analysis reports that strengthen reliability, accelerate incident response, and reinforce mission assurance for production model access across all security networks.
• Performs other duties as assigned. Required Skills • Current Secret security clearance with the ability to obtain and maintain a Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI).
• 10 or more years of progressive experience in systems engineering, platform operations, or ML/AI infrastructure roles, with a demonstrated focus on observability, telemetry, and monitoring in classified or federal government cloud environments.
• Hands-on experience designing and implementing observability pipelines using industry-standard tooling such as OpenTelemetry, Prometheus, Grafana, Elastic, Splunk, or Amazon CloudWatch, including instrumentation of AI/ML model-serving runtimes and data pipelines.
• Experience operating across multi-enclave environments, including NIPRNet, SIPRNet, and JWICS, with demonstrated ability to adapt telemetry and observability architectures to cross-domain constraints and multi-level security requirements.
• CompTIA Cloud+ certification or equivalent, demonstrating foundational knowledge of cloud infrastructure, security, and operational monitoring standards.
• Strong problem-solving and decision-making capabilities, with a proven ability to weigh the relative costs and benefits of potential actions and identify the most appropriate solution.
• Highly developed interpersonal and oral/written communication skills, with the ability to effectively and professionally interact with a diverse set of stakeholders (from peers to end-users to executive management). Desired Skills • Active Top Secret (TS) security clearance with Sensitive Compartmented Information (SCI) eligibility.
• Advanced cloud certification such as AWS Solutions Architect (Professional), AWS DevOps Engineer (Professional), or an equivalent credential demonstrating deep expertise in cloud-native observability and infrastructure-as-code practices in GovCloud or classified cloud environments.
• Practical experience with AI/ML model monitoring concepts including model drift detection, performance degradation alerting, and model validation pipelines using frameworks such as TensorFlow, PyTorch, or MLflow.
• Familiarity with Zero Trust Architecture principles and Risk Management Framework (RMF) requirements as they apply to telemetry data handling, anomaly detection, and continuous monitoring in DoW-compliant environments.
• Experience contributing to DevSecOps pipelines and CI/CD workflows in support of production AI/ML model deployment, including integration of observability gates at promotion checkpoints across development, test, and production environments. ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law. is the federal segment of , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies. Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow. We value: * Attracting and developing top talent and high-performing teams * Fostering a culture that is engaging, accountable, and mission-driven