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Remote Observability Engineer Jobs in Renton, WA

This is a remote position; however, the candidate must reside within 30 miles of one of the ... Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and ...

Senior Backend Engineer - AI Platform

Seattle, WA · On-site +1

$139.40K - $183.80K/yr

This is a remote position; however, the candidate must reside within 30 miles of one of the ... Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and ...

Infrastructure Engineering Team Lead

Seattle, WA · On-site +1

$122.30K - $160.50K/yr

... observability, and SRE. * Own operational execution for SOC 2 Type II and ISO 27001:2022 (evidence ... Remote positions: Alaska, Delaware, Hawaii, Mississippi, Nebraska, Montana, New Hampshire, West ...

Senior Backend Engineer - AI Platform

Seattle, WA · On-site +1

$139.40K - $183.80K/yr

This is a remote position; however, the candidate must reside within 30 miles of one of the ... Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and ...

We're based in Seattle and work 4 days a week in the office (one day remote). We're growing fast ... Build for production with attention to observability, monitoring, and testability from day one

New

Senior Software Engineer

Seattle, WA · On-site +1

$139.40K - $183.80K/yr

We're based in Seattle and work 4 days a week in the office (one day remote). We're growing fast ... Build for production with a focus on observability, monitoring, and testability from day one

New

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Remote Observability Engineer information

See Renton, WA salary details

$42.7K

$130.3K

$215.4K

How much do remote observability engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for remote observability engineer in Renton, WA is $130,327.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,400.00 and $170,400.00 per year, depending on experience, location, and employer.

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 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 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 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 job categories do people searching Remote Observability Engineer jobs in Renton, WA look for? The top searched job categories for Remote Observability Engineer jobs in Renton, WA are:
What cities near Renton, WA are hiring for Remote Observability Engineer jobs? Cities near Renton, WA with the most Remote Observability Engineer job openings:
Software Engineer 2 - AI Platform

Software Engineer 2 - AI Platform

WEX

Seattle, WA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


WEX Inc. rating

7.5

Company rating: 7.5 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

10th of 17 rated payment service providers


Job description

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Boston, MA; San Francisco Bay Area, CA; Dallas, TX; Salt Lake City, UT; Seattle, WA; and Portland, MEAbout the Team/Role

We are seeking a Software Engineer in the North America Mobility organization. This role will sit in the Platform team that focuses on building AI Platform to support the feature development team to build robust features faster. You will contribute to the architecting and realization of our next-generation Agentic AI Platform. Within this capacity, you will be responsible for the design, development, and deployment of autonomous AI agents, skills, MCP servers, AI tools engineered for advanced reasoning, strategic planning, and the orchestration of intricate financial and operational workflows. Operating at the vanguard of generative AI, distributed systems, and fintech, you will empower WEX to deliver highly intelligent, proactive solutions to an expansive global user base.

Our Platform team is dedicated to architecting scalable, robust, and maintainable UI and API platform solutions that empower internal feature development teams to build at velocity. Within the NAM Mobility ecosystem, our products facilitate strategic credit issuance to fleet organizations and their workforce through WEX-branded or co-branded credit instruments, accepted across a vast network of fueling stations and merchant partners. We provide fleet managers and operators with advanced spend orchestration capabilities, encompassing fuel discounts and sophisticated spend controls that permit precise configuration of merchant restrictions, transaction limits, and velocity thresholds to optimize operational efficiency.

How you'll make an impact:
  • Design, develop, and maintain robust, scalable, and high-performance object oriented code in our backend services.

  • Develop public REST APIs using Java and internal gRPC APIs for inter-service and inter-system communication.

  • Craft systems designs, lead design decisions, and drive alignment with other senior engineers.

  • Write automated unit tests, integration tests, end-to-end tests, concurrency tests, load/performance tests.

  • Analyze existing systems to identify bottlenecks, tech debt, and implement scalability, and stability improvements.

  • Implement automation for testing, monitoring, healing, and scaling applications, continuous integration and deployment to reduce time to market.

  • Collaborate with cross-functional teams, including product managers, designers, and other engineers, to define and implement new features.

  • Conduct code reviews (comment, approve, seek revisions, merge), mentor junior and mid-level engineers, and actively promote engineering best practices.

  • Dive deep and troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure lasting performance and reliability.

  • Conduct objective and comparative analyses of competing technologies to advise the team of pros and cons of a technology solution.

  • Maintain robust documentation (design docs, run books, change management docs, and readiness plans).

  • Provide live-site support for production applications by monitoring systems, ensuring rapid incident resolution, and driving continuous improvement.

  • Drive cross-team projects as a single-threaded-owner (STO) or tech lead, and actively unblock other engineers to make progress.

Agentic AI & Intelligent Systems :

  • Design and build agentic AI systems and services, enabling autonomous workflows, reasoning, and task execution within Mobility platforms.

  • Develop AI agents from scratch, including orchestration, tool usage, memory, and multi-step decision-making capabilities.

  • Implement and scale multi-agent architectures to support complex, distributed use cases across payments and fleet ecosystems.

  • Integrate systems using Model Context Protocol (MCP) or similar frameworks to enable secure and scalable interaction between AI agents, APIs, and enterprise data sources.

  • Build and optimize LLM-powered services (e.g., OpenAI APIs, LangChain) for production-grade performance, reliability, and cost efficiency.

  • Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and compliance of AI-driven systems.

  • Design solutions for context management, memory, and retrieval-augmented generation (RAG) to enhance agent effectiveness.

Experience you'll bring:
  • Bachelor's degree in Computer Science or Software Engineering

  • 2-5 years of professional experience in software engineering

  • Strong understanding of data structures and algorithms, object-oriented design, and problem-solving skills

  • Expertise in designing and developing internet-scale services with scalability, availability, security, and reliability design tenets

  • Excellent written and verbal communication skills, and a collaborative and empathetic mindset

  • Proficiency in backend development, with expertise in Java or C#, frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL

Agentic AI & MCP Experience:

  • Hands-on experience building or contributing to AI/LLM-powered applications or agent-based systems

  • Familiarity with agent frameworks, tool-use patterns, and orchestration of LLM workflows

  • Experience integrating AI systems with external tools/APIs using MCP or similar protocols

  • Understanding of prompt engineering, embeddings, and vector-based retrieval systems

  • Experience designing systems for scaling AI workloads in production environments

Preferred Qualifications
  • Master's degree in computer science or software engineering

  • 3+ years of experience in software engineering

  • Experience with Python, Java, event-driven architecture and tools like Kafka

  • Experience working on card payments

  • Familiarity with cloud-native architecture (containerization using tools such as Docker and Kubernetes)

  • Awareness of API security and PCI DSS compliance requirements

  • Ability to work on existing codebase, contribute improvements, and adapt to legacy systems' constraints

Nice to Have (AI Focus):

  • Experience building AI skills & deploying AI solutions to production environments

  • Experience building production-grade AI agents or copilots

  • Familiarity with multi-agent systems and distributed AI architectures

  • Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)

  • Knowledge of AI evaluation techniques, safety practices, and responsible AI principles

The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $96,100.00 - $115,500.00

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