Customer Success Engineer
TLDR
Act as a pivotal technical strategist within an elite sales organization, leading the strategic adoption of advanced AI technologies and observability while ensuring long-term customer success.
Architect Value & Loyalty: Develop, execute, and continuously iterate on tailored customer strategies that maximize ROI, deepen platform adoption, and cement long-term brand loyalty.
Build Trusted Technical Alliances: Foster deep, lasting relationships with key technical stakeholders, acting as their ultimate problem-solver and guiding them step-by-step through complex architectural implementations.
Fuel Revenue Growth: Champion and execute hands-on Proof of Concepts (POCs) for new features. You will proactively spot expansion opportunities to upsell and cross-sell our agentic AI and observability suites, directly driving incremental revenue.
Master the Onboarding Experience: Ensure a flawless, world-class onboarding journey, eliminating early friction and setting customers up for long-term operational success on Logz.io.
Proactively Optimize Adoption: Keep a pulse on usage analytics and adoption patterns, proactively diagnosing potential bottlenecks or drop-offs before they affect the customer, and executing swift strategies to course-correct.
Scale Knowledge & Enablement: Create premium, self-service technical resources—including deep-dive knowledge bases, strategic FAQs, and video tutorials—empowering customers to master our platform independently.
Architect Automated Onboarding: Build and refine automated onboarding workflows that guide engineering teams through step-by-step setup, pairing automation with personalized, high-touch guidance tailored to their specific architecture.
Own the Journey Milestones: Maintain a proactive communication loop with key clients, executing strategic touchpoints when they complete onboarding, hit major usage milestones, or approach renewal cycles.
Analyze Usage Behavior: Dive into customer data, tracking usage patterns and system behaviors to instantly flag underutilization, detect hidden friction points, or catch technical roadblocks before the customer does.
Champion the Customer Voice: Establish feedback loops and collaborative sessions to gather deep insights into the user experience, funneling critical product feedback straight to our engineering and product teams.
Deliver Strategic Recommendations: Act as a trusted advisor by analyzing a customer's unique usage history to deliver hyper-personalized product, feature, and architectural optimization recommendations.
Automate the Mundane: Constantly look for ways to streamline your own workflows, automating repetitive account management tasks so you can focus on high-value, high-impact technical strategy.
Our Must-Haves:
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Proven Track Record: 3+ years of experience in a highly technical, customer-facing role such as a Customer Success Engineer, Technical Account Manager (TAM), or Solutions Engineer.
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Domain Expertise: Deep industry knowledge in at least one of the following spaces: SaaS infrastructure, cloud solutions (AWS, Azure, GCP), observability technologies (logs, metrics, traces), or advanced data architecture.
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Elite Customer-Facing Skills: Exceptional ability to lead advanced technical workshops, coach engineering teams, navigate high-stakes discussions, and defuse technical conflicts. You must excel at translating complex architectural concepts into clear, actionable, and executive-friendly insights.
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Flawless Communication: Outstanding written and verbal professional communication skills in English.
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The "Go-Getter" Mindset: A positive, self-starting attitude with an entrepreneurial drive. You don’t just meet expectations; you are passionate about going the extra mile to deliver absolute value.
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Educational Foundation: A BA/BSc degree in computer science, software engineering, or equivalent practical hands-on experience.
Logz.io builds an Open 360™ Observability Platform that leverages AI to streamline the troubleshooting process for engineering teams. It's designed for companies seeking a cost-effective, efficient way to monitor and optimize their distributed systems, eliminating the complexities traditionally associated with observability.