Solutions Engineer

Logz.io; Boston (MA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Logz.io is redefining observability for AI-driven environments in Boston, with hybrid work arrangement and a strong emphasis on technical excellence. The Solution Engineer will partner with Sales and Account Managers, leading deep technical engagements, POCs, and validation to demonstrate product value and drive adoption and expansion.

This role requires 2+ years in a customer-facing technical role, expertise in SaaS infrastructures and cloud architectures, and excellent English communication.

Qualifications

• 2+ years in solution engineering, TAM, or DevOps with customer-facing experience.
• Deep SaaS infrastructure & cloud architecture experience (AWS/Azure/GCP).
• Excellent English written and verbal communication skills.
• BA/BSc in Computer Science, Software Engineering, or equivalent deep technical experience.

Responsibilities

• Architectural ownership: manage all technical touchpoints for strategic customers, driving onboarding and advanced enablement.
• Value optimization: analyze pipelines to develop technical strategies that maximize observability value and ROI.
• Technical stakeholder management: build relationships with DevOps, SRE, and engineering leaders to diagnose challenges and design production-ready solutions.
• POCs & technical validation: partner with Sales to run technical POCs and validate use cases to support purchasing decisions.
• Technical expansion & upsell: identify opportunities for upsell by uncovering new use cases and increased usage, including agentic AI solutions.

Skills

Solution engineering

Cloud architectures

Observability solutions

Customer-facing communication

Problem solving

Education

BA/BSc in Computer Science or related

Tools

AWS

Azure

GCP

OpenTelemetry

Job description

At Logz.io, we’re redefining observability for the age of AI. Trusted by 1,000+ customers worldwide, our platform helps engineering teams monitor, troubleshoot, and secure complex cloud environments. Now, with OrionIQ, we’re taking the next step toward AI-powered observability that doesn’t just detect problems, but helps teams understand and resolve them.

The Solution Engineer is a highly technical, core member of the sales and customer success organization, aligning our cutting-edge observability and agentic AI technologies with our enterprise customers' architectures. We are customer-obsessed, highly technical, and foster a team culture that is entrepreneurial, professional, and fun.

In this role, you will partner closely with Sales and Account Managers, bringing deep technical expertise to customer engagements, POCs, and solution validation. You will play a key role in demonstrating product value, driving successful adoption, and identifying technical opportunities for upsell and cross-sell, helping expand customer usage and drive revenue growth.

• Location: Hybrid (3 days from the office)
• Workweek: Monday-Friday

Responsibilities

• Architectural Ownership: Manage all technical touchpoints for strategic customers, driving deep-tech onboarding, advanced enablement, architectural workshops, and complex issue resolution.
• Value Optimization: Analyze customer data pipelines and infrastructures to develop and execute technical strategies that maximize observability value and ROI.
• Technical Stakeholder Management: Build deep technical peer relationships with DevOps, SRE, and Engineering leaders, diagnosing complex infrastructure challenges and designing production-ready solutions.
• POCs & Technical Validation:Partner with Sales to execute technical POCs, validate customer use cases, demonstrate product value, and address technical blockers to support purchasing and expansion decisions.
• Technical Expansion & Upsell: Identify technical opportunities for upsell and cross-sell by uncovering new use cases, increased usage potential, and customer needs for additional modules, including agentic AI solutions. Partner with Sales to validate these opportunities and demonstrate their technical value.
• Advanced Deployment: Ensure a frictionless, deeply integrated onboarding process for enterprise customers, managing complex log/metric/trace routing and agentic AI deployments.
• Adoption Analytics: Monitor deep-tech adoption patterns and infrastructure usage, proactively debugging systemic bottlenecks, scaling friction, or implementation barriers.

What Your Day-to-Day Will Look Like

• Manage customer technology interactions: Support technical discovery, solution demonstrations, POCs, onboarding, integration, enablement, implementation assistance, and AI use case adoption.
• Automating Integration Workflows: Design and implement automated, scalable onboarding pipelines and configuration workflows to guide enterprise environments through seamless setup.
• Proactive Architecture Reviews: Conduct deep-dive engineering check-ins around critical milestones (e.g., post-onboarding, scaling peaks, or architecture reviews) to ensure optimal system performance.
• Telemetry & Infrastructure Audits: Analyze customer data volume, telemetry pipeline health, and behavioral patterns to catch underperforming configurations or indexing issues before they impact the customer.
• Feedback Integration: Gather technical feedback, feature gaps, and product limitations from engineering stakeholders to advocate for and collaborate with internal product and R&D teams.
• Technical Upsell Engineering: Analyze data ingestion and infrastructure usage to engineer custom product/feature recommendations tailored to the customer's specific technical scale, with a focus on agentic workflows.

Requirements

• Experience: 2+ years of experience as a solution engineer, technical account manager (TAM), or DevOps engineer with strong customer-facing capabilities.
• Domain Expertise: Extensive hands-on technical experience in SaaS infrastructure, cloud architectures (AWS/Azure/GCP), observability solutions (log management, APM, tracing, and OpenTelemetry), and agentic solutions.
• Technical Communication: Strong customer-facing engineering skills—expert at training engineering teams, whiteboarding complex cloud topologies, resolving technical roadblocks, and translating deep-tech architectures into clear business value.
• Language Skills: Exceptional written and verbal professional communication skills in English.
• Mindset: Driven, self-starter technical professional with a passion for problem-solving and a desire to constantly push boundaries in AI and observability technology.
• Education: BA/BSc degree in Computer Science, Software Engineering, or equivalent deep technical experience.