Senior Support Engineer - India

Responsibilities

• Support Queue Ownership and Customer Success: Own and manage the complete support queue, working through high-volume technical tickets with a focus on driving customer success. Process requests efficiently while maintaining detailed documentation and follow-up protocols. Prioritize tickets based on customer impact and severity, ensuring SLAs are met and customers receive timely technical assistance for their AI gateway integration challenges.
• Root Cause Diagnosis and Problem Resolution: Conduct thorough investigation of customer issues to identify underlying technical causes rather than applying surface-level fixes. Analyze error logs, API responses, and system configurations to understand problem dependencies. Document findings with technical depth and clarity to build institutional knowledge and prevent recurring issues across the customer base.
• Issue Reproduction and Verification: Reproduce customer issues within their specific environments and configurations to validate problems and develop targeted solutions. Set up test environments that mirror production constraints faced by customers. Verify that fixes resolve issues comprehensively without introducing regressions or edge case failures.
• Engineering Contribution Through Pull Requests: Identify product bugs and feature improvement opportunities identified through support interactions. Submit well-documented pull requests with bug fixes, improvements, and documentation updates to the core LiteLLM platform. Collaborate with engineering teams to validate changes and ensure solutions are implemented efficiently and maintain code quality standards.
• Customer Advocacy and Technical Feedback: Serve as the technical voice of customers within the organization, translating support findings into actionable product feedback for engineering and product teams. Identify patterns in customer issues that indicate product gaps, usability challenges, or missing features. Provide recommendations for product improvements based on real-world usage patterns and customer needs.
• Technical Documentation and Knowledge Sharing: Create and maintain comprehensive technical documentation, troubleshooting guides, and FAQ resources based on commonly encountered issues. Share solutions and best practices with the support team and broader organization. Contribute to internal knowledge bases and help documentation that accelerate resolution times and improve customer self-service capabilities.

Benefits

• Competitive Salary with Performance Incentives

  Market-competitive compensation package reflecting your technical expertise and impact on customer success. Opportunity for performance bonuses tied to support quality metrics and customer satisfaction.

• Fast-Paced Growth Environment

  Work at a rapidly growing company serving enterprise customers like Adobe, Netflix, and NASA. Continuous opportunities to expand your technical knowledge as the AI/LLM space evolves and new integrations are added.

• Deep Technical Ownership

  Significant autonomy and ownership over support domain with ability to directly influence product development through bug reports and feature requests. Your technical insights directly shape the platform's direction.

• Engineer-to-Engineer Collaboration

  Work directly with LiteLLM's engineering team on bug fixes, feature validation, and technical discussions. Opportunity to contribute code through pull requests and participate in engineering decisions.

• Exposure to Cutting-Edge AI Technology

  Daily interaction with the latest large language models, AI integration patterns, and emerging AI/ML practices. Build expertise in one of the most dynamic and rapidly evolving technology sectors.

• Remote-First Work Arrangement

  Flexible work environment with remote-first approach, allowing you to maintain work-life balance while working on impactful technical problems from India.

• Continuous Learning and Development

  Access to technical resources, training, and conference opportunities to deepen expertise in AI platforms, LLMs, and software engineering best practices. Budget for professional development and certifications.