Company Overview

Observe Inc is a leading AI-powered observability company that delivers modern, scalable observability solutions built on an innovative data lake architecture. Our platform combines a cost-effective streaming data lake with a powerful knowledge graph and AI SRE-driven workflows, enabling organizations to troubleshoot faster at drastically lower cost than traditional solutions. We’ve experienced rapid growth, tripling revenue and doubling our enterprise customer base, with industry-leading 180% net revenue retention.

Position Summary

We are seeking an experienced Implementation Engineer to lead customer migrations from existing observability and monitoring solutions (Splunk, Sumo Logic, Datadog, New Relic, ELK, CloudWatch, Azure App Insights, etc.) to the Observe platform. This role combines deep technical expertise in observability technologies with customer-facing implementation skills to ensure successful, smooth transitions that maximize customer value and platform adoption.

Key Responsibilities

• Migration Planning & Strategy - Conduct comprehensive assessments of customer observability infrastructure, develop detailed migration plans for complex multi-tool environments handling up to 100TB/day+ data volumes, and design phased approaches that minimize business disruption while mapping technical deliverables to business value.
• Technical Implementation - Configure and deploy Observe platform components including data ingestion pipelines, dashboards, and alerting using OPAL and OpenTelemetry-based data collection, while collaborating with Forward Deployed Engineers to optimize the streaming data lake architecture and articulate how Observe’s Knowledge Graph and AI technology maximize customer value.
• Data Migration & Integration - Execute large-scale data migrations from legacy platforms (Splunk, Datadog, New Relic, Sumo Logic), transforming existing dashboards, queries, and alerting rules to Observe equivalents while converting legacy query languages to OPAL syntax and ensuring data continuity and accuracy throughout the migration.
• Customer Enablement & Training - Conduct hands-on training sessions on Observe platform capabilities including OPAL query language, develop custom training materials, guide customers through exploratory data analysis and troubleshooting workflows, and enable teams to leverage Observe AI SRE capabilities for observability investigations.
• Platform Optimization - In collaboration with Forward-Deployed Engineers, tune data ingestion and processing pipelines for optimal performance, implement cost optimization strategies, optimize query performance and dashboard responsiveness, and establish data governance and access control frameworks.
• Cross-functional Collaboration - Partner with Sales Engineering, Customer Success, Product teams, and Support to scope technical requirements, ensure long-term platform adoption, provide customer feedback for feature development, and coordinate technical issue resolution and knowledge transfer.

Required Qualifications

Technical Expertise

5+ years of hands-on experience with enterprise observability platforms (Splunk, Datadog, New Relic, Sumo Logic, ELK), strong knowledge of cloud platforms (AWS, GCP, Azure) and containerized environments (Kubernetes, Docker). Proficiency in query languages (SPL, PromQL, etc.). Understanding of OpenTelemetry standards, experience with log aggregation, metrics collection, distributed tracing, APM, Exposure to Infrastructure-as-Code tools, API integration. Solid grasp of observability best practices including cardinality management and SRE principles.

Communication & Collaboration

Excellent verbal and written communication skills with both technical and non-technical stakeholders, presentation abilities for executive-level discussions and technical deep-dives, project management experience in driving complex customer-facing engagements, cross-functional collaboration skills across engineering, sales, and customer success teams, and strong documentation skills for creating implementation guides, runbooks, and best practices.

Education & Certifications

Bachelor’s degree in Computer Science, Engineering, Information Technology, or related technical field (or equivalent professional experience). Cloud platform certifications (AWS Solutions Architect, GCP Professional Data Engineer, Azure Data Engineer). Observability platform certifications (Splunk Core Certified User/Admin, Datadog), and infrastructure certifications (Kubernetes CKA/CKAD, Docker, Terraform) preferred.

Location & Travel

Remote-first position with up to 25% travel for customer implementations, training, and team collaboration, requiring time zone flexibility for global customer support during critical migration phases.