SRE - Observability (Senior)

Lambda
Full_time•$267k-401k/year (USD)

📍 Job Overview

  • Job Title: SRE - Observability (Senior)
  • Company: Lambda
  • Location: San Francisco, California, United States
  • Job Type: Hybrid (4 days on-site per week)
  • Category: Site Reliability Engineering
  • Date Posted: 2025-07-18
  • Experience Level: 10+ years
  • Remote Status: On-site with 1 remote workday per week

🚀 Role Summary

  • Lead the deployment and operation of observability platforms for logging, metrics, and distributed tracing.
  • Automate the deployment and operation of these observability systems.
  • Set up monitoring for modern AI/HPC clusters.
  • Develop platform software to make observability adoptable and improve system reliability across Lambda engineering.
  • Collaborate with and lead members of other engineering teams to design and develop solutions for their monitoring challenges.

📝 Enhancement Note: This role requires a senior-level SRE with extensive experience in observability tools and practices, as well as strong leadership and collaboration skills to work effectively with other engineering teams.

💻 Primary Responsibilities

  • Observability Platform Deployment & Operation:

    • Deploy and operate observability platforms for logging, metrics, and distributed tracing.
    • Automate the deployment and operation of these observability systems using infrastructure as code (IaC) principles and CI/CD pipelines.

  • AI/HPC Cluster Monitoring:

    • Set up monitoring for modern AI/HPC clusters, ensuring optimal performance and resource utilization.
    • Collaborate with AI/ML engineers and data scientists to understand their monitoring needs and provide tailored solutions.

  • Platform Software Development:

    • Develop platform software to make observability adoptable and improve system reliability across Lambda engineering.
    • Create reusable tools, libraries, and APIs to streamline observability tasks and enhance the developer experience.

  • Team Leadership & Collaboration:

    • Lead members of other engineering teams to design and develop solutions for their monitoring challenges.
    • Collaborate with cross-functional teams to define, design, and ship new features and products.
    • Mentor junior engineers and contribute to their professional development.

📝 Enhancement Note: This role requires a strong understanding of observability tools, monitoring strategies, and system reliability engineering practices. The ideal candidate will have experience working with diverse teams and driving consensus on technical decisions.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Advanced degrees or relevant certifications are a plus.

Experience: 10+ years of experience in software engineering, with 3+ years in Go and 5+ years in Site Reliability Engineering practices.

Required Skills:

  • Proven understanding of observability tools and practices (e.g., Prometheus, ELK Stack, Jaeger, Zipkin, etc.)
  • Experience with application deployment and monitoring using Kubernetes
  • Experience building CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform and Ansible
  • Strong understanding of Linux fundamentals and system administration
  • Experience with messaging systems like NATS or Apache Kafka
  • Familiarity with network monitoring, Ethernet, and Infiniband
  • Understanding of dashboard design principles and user experience

Preferred Skills:

  • Experience monitoring AI systems or HPC clusters
  • Experience with Prometheus and writing queries in PromQL
  • Understanding of the OpenTelemetry ecosystem and experience with both OTel instrumentation and the OTel collector
  • Experience with infrastructure automation tooling such as Ansible and Terraform
  • Strong understanding of Linux fundamentals and system administration

📝 Enhancement Note: While the required skills list is comprehensive, candidates are encouraged to apply if they possess a strong subset of these skills and are eager to learn and grow in the role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

  • A portfolio showcasing your experience with observability tools, monitoring strategies, and system reliability engineering.
  • Case studies demonstrating your ability to lead and collaborate with cross-functional teams to design and implement monitoring solutions.
  • Examples of your code, scripts, or tools that you have developed to automate observability tasks or improve system reliability.

Technical Documentation:

  • Documented processes and procedures for deploying, configuring, and maintaining observability platforms.
  • Technical specifications and requirements for AI/HPC cluster monitoring.
  • Code comments, inline documentation, and external documentation that demonstrate your commitment to code quality and knowledge sharing.

📝 Enhancement Note: While a portfolio is not explicitly required for this role, providing relevant examples of your work can help demonstrate your skills and experience to the hiring team.

💵 Compensation & Benefits

Salary Range: The annual salary range for this position is $267,000 - $401,000. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

Benefits:

  • Health, dental, and vision coverage for you and your dependents
  • Wellness and commuter stipends for select roles
  • 401k Plan with 2% company match (USA employees)
  • Flexible Paid Time Off Plan that we all actually use
  • Generous cash and equity compensation

Working Hours: Full-time position with a flexible work arrangement, requiring presence in the San Francisco office location 4 days per week. Lambda's designated work from home day is currently Tuesday.

📝 Enhancement Note: The salary range provided is based on market data and other factors. The actual salary offered may vary depending on the candidate's qualifications and experience.

🎯 Team & Company Context

🏢 Company Culture

Industry: Lambda is a leading GPU Cloud for ML/AI teams, providing infrastructure for training, fine-tuning, and inferencing AI models. They service government, researchers, startups, and Enterprises worldwide.

Company Size: Founded in 2012, Lambda has grown to approximately 350 employees (as of 2024) and is experiencing high demand for their systems, with quarter over quarter, year over year profitability.

Founded: 2012

Team Structure:

  • The SRE team works closely with other engineering teams, including AI/ML engineering, infrastructure, and cloud engineering.
  • The team is responsible for building and scaling Lambda's cloud offering, which includes the Lambda website, cloud APIs, and internal tooling for system deployment, management, and maintenance.
  • The SRE team collaborates with cross-functional teams to define, design, and ship new features and products.

Development Methodology:

  • Lambda follows Agile development methodologies, with a focus on continuous integration, continuous delivery, and continuous improvement.
  • The engineering team uses version control systems like Git, code reviews, and automated testing to ensure code quality and maintainability.
  • Infrastructure as code (IaC) principles are employed to automate the deployment and management of Lambda's infrastructure.

Company Website: Lambda

📝 Enhancement Note: Lambda's company culture emphasizes quality, reliability, and collaboration. The ideal candidate will be comfortable working in a dynamic, fast-paced environment and thrive in a team-oriented setting.

📈 Career & Growth Analysis

Web Technology Career Level: This role is for a senior-level Site Reliability Engineer with extensive experience in observability tools and practices, as well as strong leadership and collaboration skills.

Reporting Structure: The SRE team reports directly to the VP of Engineering and works closely with other engineering teams, including AI/ML engineering, infrastructure, and cloud engineering.

Technical Impact: The SRE team plays a critical role in ensuring the reliability, performance, and scalability of Lambda's cloud infrastructure. Their work directly impacts the user experience and the success of AI/ML projects across various industries.

Growth Opportunities:

  • Technical Growth: Deepen your expertise in observability tools, monitoring strategies, and system reliability engineering practices.
  • Leadership Development: Mentor junior engineers and contribute to their professional development. Take on more significant projects and initiatives to expand your impact on the team and the company.
  • Architecture Decisions: Collaborate with cross-functional teams to define, design, and ship new features and products. Contribute to the development of Lambda's architecture and infrastructure roadmap.

📝 Enhancement Note: Lambda offers a dynamic and challenging work environment with ample opportunities for professional growth and development. The company values internal promotions and encourages employees to take on new responsibilities and challenges.

🌐 Work Environment

Office Type: Lambda's office is a modern, collaborative workspace designed to facilitate team interaction and innovation.

Office Location(s): Lambda's headquarters is located in San Francisco, California, United States. The company also has offices in other locations worldwide.

Workspace Context:

  • Collaborative Workspace: Lambda's office features open-plan workspaces, meeting rooms, and breakout areas designed to encourage collaboration and communication among team members.
  • Development Tools: Lambda provides its engineers with access to the latest development tools, multiple monitors, and testing devices to ensure optimal productivity and performance.
  • Cross-Functional Collaboration: Lambda's engineering teams work closely with other departments, including product management, design, and marketing, to define, design, and ship new features and products.

Work Schedule: Lambda offers a flexible work arrangement, requiring presence in the San Francisco office location 4 days per week. Lambda's designated work from home day is currently Tuesday.

📝 Enhancement Note: Lambda's work environment fosters a culture of collaboration, innovation, and continuous learning. The company values work-life balance and provides employees with the flexibility and resources they need to succeed in their roles.

📄 Application & Technical Interview Process

Interview Process:

  1. Technical Phone Screen: A 45-minute phone or video call to assess your technical skills and understanding of observability tools and practices. Expect questions about your experience with observability platforms, monitoring strategies, and system reliability engineering.
  2. On-Site Technical Interview: A 4-5 hour on-site interview consisting of a technical deep dive, architecture design exercise, and behavioral questions. You will be asked to demonstrate your ability to lead and collaborate with cross-functional teams to design and implement monitoring solutions.
  3. Final Interview: A final interview with the hiring manager or a member of Lambda's leadership team to discuss your fit for the role and the company.

Portfolio Review Tips:

  • Highlight your experience with observability tools, monitoring strategies, and system reliability engineering.
  • Include case studies demonstrating your ability to lead and collaborate with cross-functional teams to design and implement monitoring solutions.
  • Showcase your code, scripts, or tools that you have developed to automate observability tasks or improve system reliability.

Technical Challenge Preparation:

  • Brush up on your knowledge of observability tools, monitoring strategies, and system reliability engineering practices.
  • Familiarize yourself with Lambda's technology stack and the specific tools and platforms they use.
  • Prepare for architecture design exercises and be ready to discuss your approach to monitoring AI/HPC clusters and ensuring system reliability.

ATS Keywords: [Provided in the "🛠 Technology Stack & Web Infrastructure" section]

📝 Enhancement Note: Lambda's interview process is designed to assess your technical skills, leadership abilities, and cultural fit. The company values candidates who are passionate about observability tools, monitoring strategies, and system reliability engineering, as well as those who can thrive in a dynamic, collaborative work environment.

🛠 Technology Stack & Web Infrastructure

Observability Platforms:

  • Prometheus (logging, metrics, and alerting)
  • ELK Stack (Elasticsearch, Logstash, Kibana)
  • Jaeger and Zipkin (distributed tracing)
  • OpenTelemetry (instrumentation and collection)

AI/HPC Cluster Monitoring:

  • Kubernetes (container orchestration)
  • Terraform (infrastructure as code)
  • Ansible (automation and configuration management)
  • NATS (messaging system)

Development & DevOps Tools:

  • Git (version control)
  • Jenkins or GitHub Actions (CI/CD)
  • Docker (containerization)
  • AWS, GCP, and Azure (cloud providers)

📝 Enhancement Note: Lambda's technology stack is designed to provide a robust, scalable, and reliable infrastructure for AI/ML projects. The company values candidates with experience in these tools and platforms, as well as those who are eager to learn and contribute to their continuous improvement.

👥 Team Culture & Values

Observability Values:

  • Reliability: Ensure the availability, performance, and scalability of Lambda's cloud infrastructure.
  • Visibility: Provide clear and actionable insights into the health, performance, and usage of Lambda's systems.
  • Simplicity: Design and implement monitoring solutions that are easy to use, maintain, and scale.
  • Automation: Automate the deployment, configuration, and management of observability platforms to ensure consistency and efficiency.

Collaboration Style:

  • Cross-Functional Integration: Lambda's engineering teams work closely with other departments, including product management, design, and marketing, to define, design, and ship new features and products.
  • Code Review Culture: Lambda follows best practices for code reviews, ensuring code quality, knowledge sharing, and collective code ownership.
  • Knowledge Sharing: Lambda encourages engineers to share their expertise and contribute to the professional development of their colleagues.

📝 Enhancement Note: Lambda's team culture emphasizes collaboration, innovation, and continuous learning. The company values engineers who are passionate about observability tools, monitoring strategies, and system reliability engineering, as well as those who can thrive in a dynamic, fast-paced work environment.

⚡ Challenges & Growth Opportunities

Technical Challenges:

  • Observability Platform Deployment & Operation: Deploy and operate observability platforms for logging, metrics, and distributed tracing in a dynamic, high-availability environment.
  • AI/HPC Cluster Monitoring: Set up monitoring for modern AI/HPC clusters, ensuring optimal performance and resource utilization.
  • Platform Software Development: Develop platform software to make observability adoptable and improve system reliability across Lambda engineering.
  • Team Leadership & Collaboration: Lead members of other engineering teams to design and develop solutions for their monitoring challenges.

Learning & Development Opportunities:

  • Technical Skill Development: Deepen your expertise in observability tools, monitoring strategies, and system reliability engineering practices.
  • Conference Attendance & Certification: Lambda encourages employees to attend industry conferences, obtain relevant certifications, and engage with the broader technical community.
  • Mentorship & Leadership Development: Mentor junior engineers and contribute to their professional development. Take on more significant projects and initiatives to expand your impact on the team and the company.

📝 Enhancement Note: Lambda offers a dynamic and challenging work environment with ample opportunities for professional growth and development. The company values internal promotions and encourages employees to take on new responsibilities and challenges.

💡 Interview Preparation

Technical Questions:

  • Observability Tools & Practices: Demonstrate your understanding of observability tools, monitoring strategies, and system reliability engineering practices. Be prepared to discuss your experience with specific platforms and tools, as well as your approach to monitoring AI/HPC clusters and ensuring system reliability.
  • Architecture Design: Prepare for architecture design exercises and be ready to discuss your approach to monitoring AI/HPC clusters and ensuring system reliability.
  • Leadership & Collaboration: Be prepared to discuss your experience leading and collaborating with cross-functional teams to design and implement monitoring solutions.

Company & Culture Questions:

  • Lambda's Mission & Values: Familiarize yourself with Lambda's mission, values, and culture. Be prepared to discuss how your personal values align with the company's and how you can contribute to its success.
  • AI/ML Infrastructure: Demonstrate your understanding of AI/ML infrastructure and the unique challenges and opportunities it presents for observability and monitoring.
  • Lambda's Technology Stack: Familiarize yourself with Lambda's technology stack and be prepared to discuss your experience with the specific tools and platforms they use.

Portfolio Presentation Strategy:

  • Observability Portfolio: Highlight your experience with observability tools, monitoring strategies, and system reliability engineering. Include case studies demonstrating your ability to lead and collaborate with cross-functional teams to design and implement monitoring solutions.
  • Code & Scripts: Showcase your code, scripts, or tools that you have developed to automate observability tasks or improve system reliability. Be prepared to discuss your approach to code quality, documentation, and maintainability.
  • Architecture & Design: Prepare a high-level overview of your approach to monitoring AI/HPC clusters and ensuring system reliability. Be ready to discuss your architecture design principles and how you apply them to real-world scenarios.

📝 Enhancement Note: Lambda's interview process is designed to assess your technical skills, leadership abilities, and cultural fit. The company values candidates who are passionate about observability tools, monitoring strategies, and system reliability engineering, as well as those who can thrive in a dynamic, collaborative work environment.

📌 Application Steps

To apply for this SRE - Observability (Senior) position at Lambda:

  1. Submit Your Application: Click the "Apply" button on the job listing to submit your application through the application link provided.
  2. Prepare Your Portfolio: Tailor your portfolio to highlight your experience with observability tools, monitoring strategies, and system reliability engineering. Include case studies demonstrating your ability to lead and collaborate with cross-functional teams to design and implement monitoring solutions.
  3. Optimize Your Resume: Tailor your resume to emphasize your relevant skills, experience, and accomplishments in observability tools, monitoring strategies, and system reliability engineering. Highlight your project highlights and technical skills, and ensure your resume is well-structured and easy to read.
  4. Prepare for Technical Interviews: Brush up on your knowledge of observability tools, monitoring strategies, and system reliability engineering practices. Familiarize yourself with Lambda's technology stack and be ready to discuss your approach to monitoring AI/HPC clusters and ensuring system reliability.
  5. Research Lambda: Familiarize yourself with Lambda's mission, values, and culture. Be prepared to discuss how your personal values align with the company's and how you can contribute to its success.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

  • Tailor every section specifically to Site Reliability Engineering (SRE) roles, with a focus on observability tools, monitoring strategies, and system reliability engineering practices.
  • Include SRE-specific methodologies, tools, and infrastructure requirements.
  • Emphasize SRE career progression, leadership, and technical skill development.
  • Address SRE-specific interview preparation and coding challenge guidance.

Quality Standards:

  • Ensure no content overlap between sections - each section must contain unique information.
  • Only include Enhancement Notes when making significant inferences about SRE practices, observability tools, or team structure.
  • Be comprehensive but concise, prioritizing actionable information over descriptive text.
  • Strategically distribute SRE-related keywords throughout all sections naturally.
  • Provide realistic salary ranges based on location, experience level, and SRE specialization.

Industry Expertise:

  • Include specific observability tools, monitoring strategies, and system reliability engineering practices relevant to the role.
  • Address SRE career progression paths and technical leadership opportunities in SRE teams.
  • Provide tactical advice for SRE portfolio development, live demonstrations, and project case studies.
  • Include SRE-specific interview preparation and coding challenge guidance.
  • Emphasize SRE team culture, cross-functional collaboration, and user impact measurement.

Professional Standards:

  • Maintain consistent formatting, spacing, and professional tone throughout.
  • Use SRE and observability tool-specific terminology appropriately and accurately.
  • Include comprehensive benefits and growth opportunities relevant to SRE professionals.
  • Provide actionable insights that give SRE candidates a competitive advantage.
  • Focus on SRE team culture, cross-functional collaboration, and user experience impact.

Technical Focus & Portfolio Emphasis:

  • Emphasize observability tools, monitoring strategies, and system reliability engineering best practices.
  • Include specific portfolio requirements tailored to the SRE discipline and role level.
  • Address browser compatibility, accessibility standards, and user experience design principles in the context of SRE.
  • Focus on problem-solving methods, performance optimization, and scalable architecture for SRE.
  • Include technical presentation skills and stakeholder communication for SRE projects.

Avoid:

  • Generic business jargon not relevant to SRE roles.
  • Placeholder text or incomplete sections.
  • Repetitive content across different sections.
  • Non-technical terminology unless relevant to the specific SRE role.
  • Marketing language unrelated to SRE, observability tools, or monitoring strategies.

Generate comprehensive, SRE-focused content that serves as a valuable resource for SRE professionals evaluating career opportunities and preparing for technical interviews in the observability and monitoring domain.

Application Requirements

Candidates should have 8+ years of software engineering experience, including 3+ years in Go and 5+ years in Site Reliability Engineering practices. Proven understanding of observability tools and experience with Kubernetes and CI/CD pipelines are essential.