Solution Engineer

Logz.io • Boston, MA

2d • Hybrid

About The Position

At Logz.io, the Solution Engineer is a highly technical, core member of the sales and customer success organization, aligning observability and agentic AI technologies with enterprise customers’ architectures. The role partners closely with Sales and Account Managers on customer engagements, proofs of concept (POCs), and solution validation. It demonstrates product value, supports successful adoption, and identifies technical opportunities for upsell and cross-sell to expand customer usage and drive revenue growth.

The position manages technical engagements and customer architectures, including onboarding, enablement, workshops, issue resolution, deployment, telemetry analysis, and adoption. It also works with engineering stakeholders to gather product feedback and collaborates with internal product and R&D teams. The role is hybrid, with three days in the office, and follows a Monday–Friday workweek.

Requirements

• At least 3 years of experience as a solution engineer, technical account manager (TAM), or DevOps/SRE engineer, with strong customer-facing capabilities.
• Hands-on technical experience in SaaS infrastructure, cloud architectures (AWS, Azure, or GCP), observability solutions (log management, APM, tracing, and OpenTelemetry), and agentic solutions.
• Strong customer-facing engineering skills, including training engineering teams, whiteboarding complex cloud topologies, resolving technical roadblocks, and translating technical architectures into business value.
• Exceptional written and verbal professional communication skills in English.
• A driven, self-starting approach, strong problem-solving skills, and interest in advancing AI and observability technology.
• BA/BSc degree in Computer Science or Software Engineering, or equivalent deep technical experience.

Responsibilities

• Manage technical touchpoints for strategic customers, including deep-technical onboarding, advanced enablement, architectural workshops, and complex issue resolution.
• Analyze customer data pipelines and infrastructure to develop and execute strategies that maximize observability value and ROI.
• Build technical peer relationships with DevOps, SRE, and Engineering leaders; diagnose infrastructure challenges and design production-ready solutions.
• Partner with Sales to execute technical POCs, validate customer use cases, demonstrate product value, and address technical blockers.
• Identify and validate technical opportunities for upsell and cross-sell, including new use cases, increased usage, additional modules, and agentic AI solutions.
• Manage enterprise onboarding and deployments, including complex log, metric, and trace routing and agentic AI deployments.
• Monitor adoption patterns and infrastructure usage, proactively debugging systemic bottlenecks, scaling friction, and implementation barriers.
• Support technical discovery, solution demonstrations, POCs, onboarding, integration, enablement, implementation assistance, and AI use case adoption.
• Design and implement automated, scalable onboarding pipelines and configuration workflows for enterprise environments.
• Conduct engineering check-ins and architecture reviews at key milestones to help ensure optimal system performance.
• Analyze customer data volume, telemetry pipeline health, and behavioral patterns to identify underperforming configurations or indexing issues.
• Gather technical feedback, feature gaps, and product limitations from engineering stakeholders and communicate them to internal product and R&D teams.
• Analyze data ingestion and infrastructure usage to develop tailored product and feature recommendations, including recommendations for agentic workflows.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level