Support Engineer
LiteLLM2 weeks ago
Location
San Francisco
Type
Full Time
Salary
USD 120,000 – 170,000
Level
Mid
Role
Support Engineer
Posted
Jul 7, 2026
Full TimeMid
The role
Summary
Support Engineer at LiteLLM, the world's leading AI Gateway platform trusted by companies like Adobe, Netflix, and NASA. This technical support role focuses on owning the support queue, diagnosing complex customer issues, and driving product success through deep technical understanding of LLM integration and gateway architecture. You'll combine customer-centric problem-solving with software engineering expertise to resolve issues at their root cause and contribute directly to product improvements.
What you'll do
Support Queue Ownership and Ticket Management: Own and manage the entire support queue, working through customer tickets systematically to drive successful product outcomes. Handle high-volume ticket throughput while maintaining quality and customer satisfaction standards. Prioritize issues based on severity and impact, ensuring critical customer blockers receive immediate attention while managing resolution timelines effectively.
Root Cause Analysis and Diagnostic Excellence: Conduct thorough technical investigations into customer-reported issues, moving beyond surface-level symptoms to identify and address underlying root causes. Employ systematic debugging methodologies to understand the complete context of problems before implementing solutions. Document findings comprehensively to prevent recurring issues and build organizational knowledge.
Environment Reproduction and Testing: Reproduce customer issues in their specific environments and configurations to validate problems and test solutions. Set up isolated test environments that mirror customer deployments, including various LLM providers, API configurations, and integration patterns. Ensure compatibility across different deployment scenarios before recommending solutions to customers.
Code Contributions and Product Improvement: Submit pull requests for bug fixes, improvements, and edge case handling identified through customer support work. Collaborate with the engineering team to implement customer-driven enhancements that improve platform reliability and developer experience. Contribute to documentation and code examples that help customers integrate with LiteLLM more effectively.
Customer Advocacy and Engineering Liaison: Serve as the technical voice of customers within the engineering organization, advocating for customer needs and translating support feedback into actionable product improvements. Communicate customer pain points, feature requests, and usage patterns to engineering leadership. Build bridges between customer experience and product development to inform roadmap priorities.
What we look for
Technical
Python ProficiencyStrong working knowledge of Python, including ability to read, understand, and debug Python code in customer environments and the LiteLLM codebase. Experience with Python debugging tools, virtual environments, and dependency management.
LLM and AI Gateway ArchitectureDeep familiarity with Large Language Model concepts, API patterns, and AI gateway architecture. Understanding of how LLM providers (OpenAI, Anthropic, Cohere, etc.) differ in their API designs, rate limiting, error handling, and latency characteristics. Knowledge of gateway functionality including request routing, load balancing, fallback mechanisms, and cost tracking.
API Integration and REST ConceptsStrong understanding of RESTful API design, HTTP methods, status codes, authentication mechanisms (API keys, bearer tokens), and error handling patterns. Experience working with API documentation, debugging API calls, and understanding request/response cycles in the context of LLM integrations.
Debugging and TroubleshootingAdvanced troubleshooting skills including log analysis, stack trace interpretation, network debugging, and systematic problem isolation. Proficiency with debugging tools such as IDE debuggers, logging frameworks, and monitoring platforms. Ability to correlate multiple data sources to identify the root cause of complex issues.
Version Control and GitWorking knowledge of Git version control, including cloning repositories, checking out branches, reviewing code changes, and understanding pull request workflows. Ability to navigate customer code repositories and understand dependency versioning issues.
Education
Bachelor's Degree in Computer Science or Related FieldFormal education in Computer Science, Software Engineering, Information Technology, or closely related discipline providing foundational knowledge of software systems and engineering principles.
Experience
Technical Support or Developer Relations Experience2-4 years of technical support, developer support, or developer relations experience in software or infrastructure companies. Experience directly supporting developers or technical users, troubleshooting complex technical issues, and owning ticket queues.
Software Development or DevOps BackgroundPrior experience as a software engineer, backend developer, DevOps engineer, or similar role that provided hands-on experience with production systems, deployment pipelines, and troubleshooting infrastructure issues. This experience directly translates to understanding customer environments and debugging complex interactions.
LLM Ecosystem FamiliarityPractical experience working with Large Language Model APIs, prompt engineering, or building AI applications. Familiarity with popular LLM providers and understanding of how these services integrate into larger applications.
Skills
Required skills
Python ProgrammingAbility to read, write, and debug Python code. Comfortable navigating Python projects, understanding dependency management, and troubleshooting runtime issues.
Technical Problem-SolvingSystematic approach to identifying and solving complex technical problems. Strong analytical skills to isolate issues, form hypotheses, and validate solutions through testing and validation.
API Integration UnderstandingDeep knowledge of how APIs work, including REST principles, authentication, rate limiting, error handling, and integration patterns. Ability to read API documentation and understand integration requirements.
Customer CommunicationExcellent written and verbal communication skills for explaining technical concepts to non-technical stakeholders. Ability to gather detailed problem information from customers and translate that into technical action items.
LiteLLM Product KnowledgeStrong working knowledge of the LiteLLM platform, including how it routes requests across LLM providers, manages authentication, handles errors, and integrates with customer applications.
System Debugging and Log AnalysisProficiency in reading and interpreting log files, stack traces, and error messages. Ability to correlate logs across multiple components to identify where issues originate and how to resolve them.
Nice to have
LangChain or LLM Framework ExperiencePrior experience with LangChain, LlamaIndex, or other LLM orchestration frameworks. Understanding of how these frameworks integrate with gateway solutions like LiteLLM to manage LLM interactions.
Docker and Containerization KnowledgeFamiliarity with Docker containers, containerized deployments, and container orchestration. Many customers run LiteLLM in containerized environments, so understanding container architecture is valuable for reproduction and diagnosis.
Monitoring and Observability ToolsExperience with monitoring platforms, logging solutions (ELK stack, Datadog, New Relic), and observability best practices. This helps understand customer deployment patterns and diagnose performance issues.
SQL Database KnowledgeBasic understanding of SQL and relational databases. Useful for troubleshooting issues related to data persistence, caching, and understanding customer data architecture.
Cloud Platform ExperienceHands-on experience with AWS, Google Cloud, or Azure. Many LiteLLM customers deploy on cloud platforms, and understanding cloud networking, IAM, and service integrations helps troubleshoot deployment issues.
Open Source ContributionPrevious contributions to open source projects, demonstrating ability to navigate unfamiliar codebases, understand project structure, and contribute meaningful improvements. LiteLLM is an open source project, so this experience is directly applicable.
Compensation & benefits
Salary
USD 120,000 – 170,000 (annual)
Stock options
Available
Benefits
Health, Dental, and Vision Coverage
Comprehensive medical, dental, and vision insurance plans covering employee healthcare needs and preventive care.
401(k) Retirement Plan with Company Match
3.5% employer match on 401(k) contributions, helping you build long-term retirement savings with company support.
Equity Compensation
Stock options or equity grants providing opportunity to participate in company growth and long-term value creation as LiteLLM scales.
Fast-Paced Growth Environment
Opportunity to work in a rapidly expanding company serving enterprise customers like Adobe, Netflix, and NASA, with direct impact on product development and customer success.
Deep Technical Ownership
Significant autonomy and responsibility for customer support operations, with direct influence on product improvements and engineering decisions based on customer feedback.
Interview process
- 1Initial Screening Call — 15-20 minute conversation with the recruiting team to discuss your background, interest in the role, and technical support experience. This call assesses general fit and communication skills.
- 2Technical Support Scenario Interview — 45-60 minute interview with a current team member focused on real support scenarios. You'll walk through how you approach debugging complex customer issues, your experience with root cause analysis, and your problem-solving methodology. Expect discussions about specific technical challenges you've faced and how you resolved them.
- 3LiteLLM Product Deep Dive — 30-45 minute conversation with a LiteLLM engineer to assess your understanding of LLM concepts, API integration patterns, and the gateway architecture. You'll discuss how the LiteLLM platform works, how it handles different LLM providers, and potential edge cases in customer deployments.
- 4Customer Advocacy and Communication Assessment — Discussion focused on how you've advocated for customers in previous roles, communicated technical issues to engineering teams, and influenced product improvements based on customer feedback. This assesses your ability to bridge customer needs and engineering priorities.
- 5Culture and Team Fit Discussion — Final conversation with a team lead or manager covering work style, collaboration preferences, growth aspirations, and alignment with LiteLLM's fast-paced, customer-focused culture. Discussion of what success looks like in the role and how you measure impact.
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LiteLLM
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LiteLLM is a platform that provides a unified interface for accessing multiple large language models (LLMs) from different providers. The company offers tools and infrastructure that enable developers and organizations to seamlessly integrate various AI models into their applications while managing costs, performance, and deployment complexity. LiteLLM operates in the artificial intelligence and developer tools market, serving businesses that need flexible access to different language models without being locked into a single provider's ecosystem.
litellm.ai
Tech Stack
Languages
PythonTypeScript/JavaScript
Frameworks
FastAPILangChainPydantic
Databases
PostgreSQLRedis
Tools
Git and GitHubPostman or Similar API Testing ToolsDockerCommand Line and Unix/Linux
Other
LLM Provider APIsAPI Gateway Architecture and PatternsLogging and Monitoring