Backend Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Backend Engineer San Francisco | OnSite Backend Engineer LiteLLM is the world's most popular AI Gateway, trusted by top companies like Adobe, Netflix, and NASA. Our platform empowers developers by providing secure, reliable access to LLMs and adjacent services, and we're looking for a Senior Backend Engineer to help us build rock-solid guardrails and observability tooling at scale. About The Role You'll focus on owning our guardrails and logging world-class. You will be in charge of the backend code that ensures all guardrail calls are consistently logged, errors are surfaced to users (not silently swallowed), and our observability instrumentation works for real-world, high-volume traffic. Your attention to detail in areas like latency metrics, logging traceability, and backend guardrail registration will directly impact user trust in our security and compliance features. Responsibilities - Build and scale our product, ensuring performance, reliability, and continuous improvement. - Ensure all guardrail and policy enforcement calls (e.g., applyguardrail) are properly logged and traceable through our SpendLogs and relevant database tables - Build and design CPU-level guardrails to cover common attacks on LLM API's / MCP servers / Agents - Identify and fix areas where silent failures occur in guardrail creation, registration, and policy application-ensuring robust error handling and transparency to end users - Work with observability integrations, including Datadog, Splunk, Prometheus, and OpenTelemetry, to maintain accurate, configurable, and usable monitoring and logging for backend systems - Enhance observability integrations to work for 1B+ requests/mo., with minimal latency overhead and no memory leaks (e.g. due to

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