Sr. Forward Deployed Engineer
$130,900–$175,000 year
HybridSan Francisco, California, United States
Job Summary
Partner with strategic customers to design, build, and deploy tailored solutions extending LogicMonitor Edwin AI, covering discovery, scoping, system design, build, rollout, and measurable adoption. Ship production applications, technical artifacts, and reusable deployment patterns while implementing REST API, webhook, and SDK integrations that normalize operational data into the platform. Build backend services and lightweight full-stack experiences using Python, JavaScript, or TypeScript, instrument telemetry across logs, metrics, and traces, and configure deployments in SaaS, hybrid cloud, and customer-managed environments. Support go-live, hypercare, and troubleshooting to drive adoption, then convert field learnings into templates, playbooks, and product feedback for core engineering teams.
Required Qualifications
- Bachelor's degree in Computer Science, Data Engineering, or a related field
- 4-7 years of experience in backend or data systems engineering
- Experience building streaming data pipelines (Kafka / Spark or any similar technology)
- Strong programming background in Java and Python, including microservice design
- Experience with ETL, data modeling, and distributed storage systems
- Demonstrated ability to ship clean, production quality code in Java or Python plus JavaScript or TypeScript
- Demonstrated ability to integrate external systems using APIs, SDKs, authentication controls, payload mapping, and schema validation
- Working knowledge of observability fundamentals, including logs, metrics, traces, dashboards, alerting, root cause investigation, and incident workflows
- Familiarity with OpenTelemetry concepts and telemetry pipelines, including how data is instrumented, collected, and routed across systems
- Working knowledge of modern cloud and deployment tooling such as AWS, Azure, or GCP, containers, Kubernetes, CI or CD, and infrastructure automation tools
- Practical exposure to AI application patterns such as LLM APIs, agents or workflows, evaluation basics, and the observability of AI systems in production
- Strong debugging judgment, systems thinking, and the ability to make progress in ambiguous customer environments
- Awareness of data governance, validation, and lineage best practices
- Strong communication and collaboration across AI, Data, and Platform teams
- Clear written and verbal communication skills, with the ability to explain technical tradeoffs to engineers, product teams, and customer stakeholders
- Candidates who currently hold valid U.S. work authorization that can be transferred to a new employer (such as certain H-1B statuses) may be considered on a case-by-case basis
Desired Qualifications
- Nice to have: ServiceNow or Jira workflows, automation tooling such as Ansible, Terraform, or Rundeck, and familiarity with MCP or similar integration patterns
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