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Remote Observability Engineer Jobs in Washington, DC

Senior Software Engineer

Ashburn, VA · Remote

$125K - $165K/yr

This is a remote position. The ideal candidate is a senior full-stack engineer who will provide ... Terraform; CI/CD; git-based code management; and observability tools. Experience designing ...

As a remote-first organization headquartered in St. Petersburg, Florida, Kobie values meaningful in ... Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or ...

Senior Engineer

Mclean, VA · On-site +1

$110K - $180K/yr

Deploy and support observability platforms using Prometheus, Grafana, Fluent Bit, Loki, Kibana, and ... Remote with a preference for candidates based in Colorado Springs, CO and McLean, VA What we will ...

DevOps Engineer

Washington, DC · On-site +1

$59.75 - $81.75/hr

Help implement and maintain observability solutions for monitoring system performance and ... We offer a hybrid work schedule to perfectly combine the benefits of remote work and the essential ...

DevOps Engineer

Washington, DC · Remote

$54 - $74/hr

Help implement and maintain observability solutions for monitoring system performance and ... We offer a hybrid work schedule to perfectly combine the benefits of remote work and the essential ...

Showing results 21-40

Remote Observability Engineer information

See Washington, DC salary details

$43K

$131.2K

$216.9K

How much do remote observability engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for remote observability engineer in Washington, DC is $131,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $171,600.00 per year, depending on experience, location, and employer.

What is a remote observability engineer?

A Remote Observability Engineer is a professional responsible for designing, implementing, and maintaining systems that monitor the health, performance, and reliability of software applications and infrastructure from a remote location. They use observability tools to collect and analyze logs, metrics, and traces, helping organizations quickly detect and resolve issues. Their work ensures that distributed systems are transparent, reliable, and efficient, often collaborating with development, operations, and security teams. Remote Observability Engineers often work from anywhere, leveraging cloud-based tools and platforms to manage complex IT environments.

What are the typical collaboration patterns for a remote observability engineer working with distributed teams?

Remote Observability Engineers frequently collaborate with software developers, DevOps teams, and IT operations to ensure systems are monitored effectively and issues are detected early. Working remotely, you'll often use communication tools like Slack, Jira, and video conferencing to coordinate incident response, discuss monitoring strategies, and review system health dashboards. Regular sync meetings and asynchronous updates are common, and you'll likely contribute to documentation and knowledge sharing to keep all stakeholders informed. Building strong communication habits is important, as much of the troubleshooting and improvement work hinges on clear coordination with multiple teams.

What are the key skills and qualifications needed to thrive as a remote observability engineer, and why are they important?

To thrive as a Remote Observability Engineer, you need strong expertise in monitoring, logging, and tracing systems, along with a background in computer science or related technical fields. Familiarity with tools like Prometheus, Grafana, ELK Stack, Datadog, and cloud platforms is typically required, as well as relevant certifications such as AWS Certified Cloud Practitioner or Google Cloud Professional DevOps Engineer. Excellent problem-solving abilities, communication skills, and a proactive mindset help you detect and resolve issues before they impact users. These competencies ensure system reliability, enable rapid incident response, and support seamless collaboration in distributed environments.

What is the difference between Remote Observability Engineer vs Site Reliability Engineer?

AspectRemote Observability EngineerSite Reliability Engineer
CredentialsKnowledge of monitoring tools, scripting, cloud platformsSame as Observability Engineer, plus SRE certifications often preferred
Work EnvironmentFocus on monitoring, logging, and tracing systems remotelyBroader scope including system reliability, incident response, and automation
Industry UsagePrimarily in tech, SaaS, cloud servicesWidely in tech, finance, and large-scale online services

The Remote Observability Engineer specializes in monitoring and analyzing system performance remotely, focusing on tools like logs and metrics. In contrast, the Site Reliability Engineer has a broader role, ensuring overall system reliability, automation, and incident management. While both roles require similar technical skills, SREs often have additional responsibilities related to system resilience and scalability.

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

The most popular types of Observability Engineer jobs in Washington, DC are:

What are popular job titles related to Remote Observability Engineer jobs in Washington, DC?

For Remote Observability Engineer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Remote Observability Engineer jobs in Washington, DC look for?

The top searched job categories for Remote Observability Engineer jobs in Washington, DC are:

Infographic showing various Remote Observability Engineer job openings in Washington, DC as of August 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 100% Remote job distribution, with an average salary of $131,228 per year, or $63.1 per hour.

Distinguished AI Engineer (Remote Eligible)

Capital One

Mclean, VA • On-site, Remote

Full-time

Posted 6 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

91st of 171 rated banks


Job description

Distinguished AI Engineer (Remote Eligible)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

  • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

  • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Capital One is open to hiring a Remote Employee for this opportunity.

The Ideal Candidate:

  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

  • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

  • You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies

  • At least 8 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

  • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

  • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems

  • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level

  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers


Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Remote (Regardless of Location): $244,700 - $279,200 for Distinguished AI Engineer


McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer


San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer


San Jose, CA: $293,600 - $335,100 for Distinguished AI Engineer








Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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