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Executive Observability Engineer Jobs in Ohio (NOW HIRING)

... observability, and configuration consistency. * Establish automated testing, release governance ... Communicate complex technical concepts clearly to both executive and engineering stakeholders.

Senior Data Engineer

Columbus, OH

$102K - $139K/yr

As a Data Engineer, you will help build,maintain, and improve the data infrastructure that powers ... observability, and documentation best practices. * Experience supporting executive reporting ...

Senior Data Engineer

Columbus, OH · On-site

$102K - $139K/yr

As a Data Engineer, you will help build, maintain, and improve the data infrastructure that powers ... observability, and documentation best practices. * Experience supporting executive reporting ...

You will own agent capabilities end-to-end, with a focus on reliability, evaluation, observability ... Ability to present and effectively communicate with Senior Leaders and Executives. * Understanding ...

You will own agent capabilities end-to-end, with a focus on reliability, evaluation, observability ... Ability to present and effectively communicate with Senior Leaders and Executives. * Understanding ...

You will own agent capabilities end-to-end, with a focus on reliability, evaluation, observability ... Ability to present and effectively communicate with Senior Leaders and Executives. * Understanding ...

Showing results 21-40

Executive Observability Engineer information

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

AspectExecutive Observability EngineerSite Reliability Engineer
CredentialsTypically requires expertise in observability tools, monitoring, and cloud platformsRequires skills in systems engineering, coding, and infrastructure management
Work EnvironmentFocuses on designing observability solutions, analyzing system health, and strategic monitoringManages system reliability, automates deployment, and maintains infrastructure
Industry UsageUsed in tech companies emphasizing system visibility and performance analysisCommon in cloud services, SaaS, and large-scale web services

The Executive Observability Engineer primarily focuses on implementing and optimizing observability tools to ensure system health, while the Site Reliability Engineer concentrates on maintaining system reliability and automating infrastructure. Both roles require technical expertise but differ in their strategic versus operational focus.

What are some common challenges executive observability engineers face when implementing organization-wide monitoring solutions?

Executive Observability Engineers often encounter challenges such as integrating diverse monitoring tools across legacy and modern systems, ensuring data consistency, and balancing comprehensive visibility with system performance. Coordinating with multiple teams to align observability goals and fostering a culture of proactive monitoring can also require strong communication and leadership skills. Successfully managing these complexities leads to more resilient infrastructure and improved incident response times.

What is an executive observability engineer?

Executive Observability Engineers are specialized IT professionals who design and manage systems that monitor, analyze, and optimize the health and performance of an organization's technology infrastructure. They focus on providing high-level visibility into applications, networks, and services, enabling executives to make data-driven decisions. These engineers implement observability tools, create dashboards, and generate reports that translate complex technical metrics into actionable business insights. Their work is crucial for ensuring system reliability, quick incident response, and continuous improvement across the organization.

What are the key skills and qualifications needed to thrive as an executive observability engineer?

To thrive as an Executive Observability Engineer, you need deep expertise in performance monitoring, distributed systems, and troubleshooting, often supported by a degree in computer science or a related field. Familiarity with observability tools such as Datadog, New Relic, Prometheus, and advanced logging systems, as well as certifications like AWS Certified DevOps Engineer, is highly beneficial. Strong analytical thinking, communication, and leadership skills set top candidates apart in this role. These skills and qualities are crucial to proactively detect issues, optimize system performance, and drive strategic decision-making across complex technical environments.
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Distinguished AI Software Engineer

Socket.dev

Dayton, OH • On-site

$180 - $240/hr

Other

This job post has expired today. Applications are no longer accepted.


Job description

Overview

FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.


FTI Defense is seeking a Distinguished AI Software Engineering Lead to serve as both a hands‑on architect and integrator for mission‑critical software and data platforms. This role is designed for a player‑coach—someone who provides technical vision, architectural oversight, and mentoring, while contributing directly to the design and development of secure, scalable, and modernized solutions. The Distinguished Engineer will act as the connective tissue between software execution teams, product and solution management, and business development, ensuring solutions are scalable, secure, and aligned with long‑term innovation goals.


Responsibilities

  • Architecture & Systems Integration Architect and deploy secure, distributed platforms supporting modular, multi‑service software environments.

  • Design and integrate APIs, microservices, and data pipelines that enable interoperability across mission, simulation, and analytical systems.

  • Define and enforce architectural principles, modularity standards, and software best practices across development teams.

  • Engineer solutions that bridge cloud, on‑prem, and classified enclaves, ensuring interoperability and compliance.

  • Cloud Engineering & DevSecOps Engineer cloud‑native solutions in AWS GovCloud or hybrid IL4–IL6 environments with strict security and accreditation requirements.

  • Implement Infrastructure-as-Code (Terraform, CloudFormation, or CDK) to automate provisioning, configuration, and accreditation workflows.

  • Build and maintain CI/CD pipelines that embed security, compliance, and automated testing from development through deployment.

  • Ensure all platform designs support zero‑trust principles, multi‑enclave deployment, and repeatable accreditation (ATO) processes.

  • Data Infrastructure & Orchestration Design or oversee large‑scale data ingestion, transformation, and orchestration environments (Kafka, Airflow, Spark, or Databricks).

  • Shape data architectures that balance throughput, latency, and cost across distributed mission environments.

  • Enable secure and efficient data access and synchronization across analytical, AI‑enabled, and simulation workloads.

  • Automation, Operationalization & Sustainment Transition software and platforms from prototype to production, ensuring maintainability, observability, and configuration consistency.

  • Establish automated testing, release governance, and performance monitoring standards for ongoing sustainment.

  • Partner with program and product leadership to align delivery with mission lifecycle requirements.

  • Security & Resilience Engineer architectures for redundancy and resilience under degraded or disconnected operational conditions.

  • Design and maintain secure enclave architectures, boundary controls, and cross‑domain integration solutions.

  • Collaborate with cybersecurity and ISSM teams to support ATO and ongoing accreditation automation.

  • Innovation & Ecosystem Integration Integrate emerging technologies, open standards, and modern frameworks into operational systems.

  • Collaborate with AI/ML, data, and simulation teams to enable model integration and inference services within production software (familiarity with MLOps concepts preferred).

  • Evaluate new tools and frameworks to improve developer productivity, performance, and automation efficiency.

  • Leadership & Mentorship Lead by example as a hands‑on technical authority, guiding design and implementation decisions.

  • Mentor software engineers and architects to raise technical standards, code quality, and architectural maturity.

  • Partner with fellow Distinguished Engineers and organizational leaders to align platform strategy with enterprise innovation goals.

  • Communicate complex technical concepts clearly to both executive and engineering stakeholders.


Education/Qualifications

**Preferring candidates close to Dayton OH, Chesapeake VA, Huntsville AL, or Colorado Springs CO. Or willing to travel to these locations and customer sites, as needed.


Required:



  • Active Secret clearance required; TS/SCI strongly preferred.

  • Bachelor’s degree in Computer Science, Software Engineering, or related technical field (Master’s preferred).

  • 10–15 years of progressive software engineering experience, with at least 5 years in a technical leadership or architecture role.

  • Proven success architecting and deploying secure, distributed, cloud‑native software platforms.

  • Deep experience with AWS GovCloud or IL4–IL6 hybrid environments.

  • Hands‑on proficiency with Infrastructure-as-Code (Terraform, CloudFormation, or CDK) and CI/CD automation.

  • Strong understanding of DevSecOps, zero‑trust principles, and mission accreditation (ATO/RMF) processes.

  • Demonstrated ability to operationalize software systems from prototype through accreditation in secure environments.

  • Strong coding experience in one or more core languages (Python, Java, C++, TypeScript).


Desired:



  • Experience developing developer‑facing APIs, SDKs, or enablement platforms for enterprise‑scale interoperability.

  • Familiarity with containerization and orchestration (Docker, Kubernetes, ArgoCD, or Rancher).

  • Awareness of MLOps and AI solution integration practices — capable of collaborating with AI/ML teams on model deployment and sustainment.

  • Proven ability to mentor engineers and influence enterprise‑level software design decisions.

  • Recognized for contributions advancing automation, performance, and platform modernization within secure environments.

  • Comfortable balancing architecture, coding, and stakeholder engagement in fast‑paced mission contexts.


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