Role Description ECS is seeking a Sr. Elastic Engineer to work remotely. This position is contingent upon additional funding. Are you passionate about building and scaling Elastic environments and eager to make an immediate technical impact? In this role, you will implement, optimize, and maintain Elastic Stack environments at scale while contributing to architecture, automation, and integrations that improve reliability, performance, and operational efficiency. We are seeking a Sr. Elastic Engineer to join our Professional team. The ideal candidate has hands-on experience with Elastic Stack and enjoys designing, coding, and deploying complex systems. You will collaborate with engineering, DevOps, cloud, and client teams to deliver resilient, high-performance Elastic solutions while maintaining visibility into system health and operational workflows. Key Responsibilities: - Design, deploy, and maintain Elastic Stack environments, including Elasticsearch, Kibana, Logstash, Beats, and Fleet. - Build and optimize ingestion pipelines, index strategies, search queries, dashboards, and automation workflows. - Write scripts, automation, and integrations (Python, PowerShell, Bash, etc.) to streamline operations, data processing, and monitoring. - Deploy Elastic across platforms, including on-premises, public cloud (AWS, Azure, GCP), GovCloud, and containerized environments (Kubernetes, Docker, OpenShift). - Leverage automation and orchestration tools such as Terraform, Ansible, CI/CD pipelines, and Docker to manage deployments and operational tasks. - Integrate Elastic with enterprise tools such as SIEMs, Splunk, CrowdStrike, and other telemetry sources. - Monitor system health, troubleshoot performance issues, and optimize for reliability and scalability. - Lead design reviews, provide guidance on Elastic best practices, and support knowledge sharing across teams. - Maintain documentation for architectures, deployment patterns, runbooks, and operational best practices. - Stay current with Elastic features, certifications, and emerging platform capabilities. Qualifications - Deep, hands-on expertise with Elastic Stack (Elasticsearch, Kibana, Logstash, Beats, Fleet). - Strong scripting and automation skills (Python, PowerShell, Bash, etc.). - Solid understanding of observability, logging, metrics, and distributed systems. - Experience designing, deploying, and optimizing production-scale Elastic environments. - Strong Linux/Unix, networking, and cloud platform knowledge (AWS, Azure, GCP). - Ability to mentor, guide, and influence engineering teams on Elastic best practices. - Outstanding verbal and written communication skills. - Willingness and ability to support domestic or international on-site engagements. - U.S. Passport required. - Must have a Secret Clearance, at minimum. Requirements - Salary Range: $170,000-$190,000 Benefits - General Description of Benefits

Role Description ECS is seeking a Sr. Elastic Engineer to work remotely. This position is contingent upon additional funding. Are you passionate about building and scaling Elastic environments and eager to make an immediate technical impact? In this role, you will implement, optimize, and maintain Elastic Stack environments at scale while contributing to architecture, automation, and integrations that improve reliability, performance, and operational efficiency. We are seeking a Sr. Elastic Engineer to join our Professional team. The ideal candidate has hands-on experience with Elastic Stack and enjoys designing, coding, and deploying complex systems. You will collaborate with engineering, DevOps, cloud, and client teams to deliver resilient, high-performance Elastic solutions while maintaining visibility into system health and operational workflows. Key Responsibilities: - Design, deploy, and maintain Elastic Stack environments, including Elasticsearch, Kibana, Logstash, Beats, and Fleet. - Build and optimize ingestion pipelines, index strategies, search queries, dashboards, and automation workflows. - Write scripts, automation, and integrations (Python, PowerShell, Bash, etc.) to streamline operations, data processing, and monitoring. - Deploy Elastic across platforms, including on-premises, public cloud (AWS, Azure, GCP), GovCloud, and containerized environments (Kubernetes, Docker, OpenShift). - Leverage automation and orchestration tools such as Terraform, Ansible, CI/CD pipelines, and Docker to manage deployments and operational tasks. - Integrate Elastic with enterprise tools such as SIEMs, Splunk, CrowdStrike, and other telemetry sources. - Monitor system health, troubleshoot performance issues, and optimize for reliability and scalability. - Lead design reviews, provide guidance on Elastic best practices, and support knowledge sharing across teams. - Maintain documentation for architectures, deployment patterns, runbooks, and operational best practices. - Stay current with Elastic features, certifications, and emerging platform capabilities. Qualifications - Deep, hands-on expertise with Elastic Stack (Elasticsearch, Kibana, Logstash, Beats, Fleet). - Strong scripting and automation skills (Python, PowerShell, Bash, etc.). - Solid understanding of observability, logging, metrics, and distributed systems. - Experience designing, deploying, and optimizing production-scale Elastic environments. - Strong Linux/Unix, networking, and cloud platform knowledge (AWS, Azure, GCP). - Ability to mentor, guide, and influence engineering teams on Elastic best practices. - Outstanding verbal and written communication skills. - Willingness and ability to support domestic or international on-site engagements. - U.S. Passport required. - Must be eligible to obtain a U.S. Security Clearance. Requirements - Salary Range: $170,000-$190,000 Benefits - General Description of Benefits

The RoleFusion Engineering is building the agentic workflow that will power how our entire engineering organization delivers software. We have stood up a suite of AI agents capable of delivering features, enhancements, and bug fixes—and we are now looking for Harness Engineers to operate that system at scale and help it continuously improve. This is not a role about building the harness from scratch. It is about becoming an expert operator of it: steering agents toward quality outcomes, translating product requirements into precise agent-ready specifications, reviewing and validating AI-generated solutions, and closing the feedback loop so the system gets smarter over time. You will be the manager in the loop—the engineer whose judgment, communication, and technical depth determines whether a feature ships with confidence. Harness Engineers at Fusion work across the full delivery lifecycle: collaborating with product and design to scope requirements, crafting the context and prompts that direct agents, reviewing output for quality and correctness, and partnering with other engineering teams as embedded technical contributors. No two days look exactly the same—and the discipline itself is evolving fast. If you are energized by operating at the frontier of how software gets built, this role is for you. Key Responsibilities• Translate feature requirements, enhancements, and product briefs into well-scoped, agent-ready specifications with clear acceptance criteria, constraints, and success conditions—including building Proof of Concepts (POCs) to validate approaches with Product Managers before full delivery begins • Operate a suite of AI agents to deliver working software—directing agents through the full delivery cycle from specification through review and validation • Review and validate agent-generated output for quality, correctness, edge case coverage, and alignment with product intent before solutions reach clients • Craft and iterate on prompts and context inputs that reliably direct agents toward high-quality outcomes across a variety of feature types • Collaborate with product managers, designers, and business stakeholders to refine requirements and ensure agents have the clarity they need to succeed • Work as an embedded technical contributor across product engineering teams, bringing agentic delivery capabilities to initiatives of varying scope and complexity • Identify recurring failure patterns in agent output and surface structured feedback to the platform team to improve harness guardrails and tooling over time • Champion quality and engineering standards in an AI-driven delivery model—advocating for rigor, transparency, and client-centered outcomes Knowledge, Skills, and Abilities• Deep, hands-on familiarity with AI coding agents and agentic workflows—including how to direct them effectively, where they fail, and how to recover when they do • Strong ability to write precise, unambiguous specifications: requirements, acceptance criteria, and constraints that agents can act on without additional clarification • Sharp technical judgment to evaluate AI-generated code and solutions—identifying gaps, regressions, and quality issues without necessarily writing the fix yourself • Experience with prompt and context engineering as a practical discipline: iterating on inputs to produce more reliable, higher-quality agent outputs • Ability to collaborate effectively across functions—translating between the language of product, design, and engineering stakeholders with ease • Comfort operating in ambiguity and adapting quickly as tooling, workflows, and best practices evolve in real time • Strong communication and documentation habits: the ability to articulate decisions, capture context, and make agent interactions auditable and reproducible Qualifications (Education and Experience)• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience) • 5+ years of software engineering experience, with a strong emphasis on directing AI coding agents to deliver production-ready software—hands-on agent management is the core of this role, not traditional coding • Demonstrated track record of delivering features or enhancements using agentic or AI-assisted workflows—not just experimenting, but shipping • Deep understanding of how large language models and coding agents behave: context windows, non-determinism, failure modes, and how harness constraints improve reliability • Experience working in enterprise B2B SaaS environments with cross-functional product and engineering teams • Familiarity with CI/CD pipelines, version control workflows, and modern software delivery practices—even if agents are doing the implementation • Experience with Microsoft Azure or Salesforce platforms is a plus, but not required Compensation & BenefitsThe annual base salary range for this position is $150,000-165,000, depending on the candidate’s experience, qualifications, and relevant skill set. This role is eligible for executive-level bonus incentives and may participate in long-term incentive programs. Fusion offers a comprehensive benefits package including medical, dental, vision, and a 401(k) plan. Fusion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, age, pregnancy, military service or discharge status, genetic information, sex, sexual orientation, gender identity, or national origin. Nothing in this job posting should be construed as an offer or guarantee of employment.

• Build and ship features and services within your team's architecture • Help migrate rapidly-prototyped applications into production-grade, well-architected cloud services • Take on development tasks that carry some ambiguity, asking good questions to close the gaps • Participate in code reviews and uphold the team's standards for engineering and operational excellence • Write, review, and update technical documentation • Collaborate across the team to deliver quality work at a steady pace