Lead Software Engineer (LMTS), Foundations

What You'll Do

• Architect & Build: Lead the design and implementation of secure, fault-tolerant, and highly available cloud infrastructure on public cloud services.
• System Optimization: Continuously improve system performance, identify bottlenecks, and deploy optimizations for smooth operation at scale for highly-trafficked services.
• CI/CD Evolution: Lead the evolution of our Continuous Integration and Deployment pipelines in a multi-service environment, reducing complexity and increasing resilience.
• Infrastructure Management: Plan and execute timely infrastructure upgrades and changes using infrastructure-as-code to enable faster execution, improved scale, and increased cost efficiency.
• Observability: Leverage tools like DataDog, Sentry, and others to monitor system infrastructure, configure alerts for anomalies, and proactively ensure system health.
• Documentation & Standards: Define, promote, and maintain runbooks, operating procedures, and system architecture diagrams. Uphold high standards of quality through rigorous testing and code reviews.
• Mentorship: Act as a force multiplier by providing technical guidance, mentoring other engineers, and fostering a culture of engineering excellence.
• Agility: Embrace a culture of flexibility and efficiency, moving fast to capture opportunities while wearing multiple hats in a startup environment

What We're Looking For

• Experience: 7+ years of experience in professional software development with a strong emphasis on backend systems, cloud platforms, and infrastructure.
• Languages: Proficiency in programming languages such as Go, Python, Typescript, or Ruby.
• Cloud & Infrastructure: Deep experience architecting secure solutions on cloud-based infrastructure (e.g., AWS, Google Cloud, or Azure).
• Infrastructure as Code (IaC): Proven experience in automated provisioning using tools like Terraform, CDK, CloudFormation, or Pulumi.
• Containerization: Experience with automated deployments using container orchestration technologies such as Kubernetes, AWS ECS, or Docker.
• Observability Tools: Strong hands-on experience with monitoring and logging tools such as DataDog, Prometheus, Grafana, or ELK.
• Database Expertise: Familiarity with SQL, RDBMS (PostgreSQL preferred), and data warehousing solutions (e.g., ClickHouse)
• AI-Assisted Development: Proficiency in AI-assisted software development (e.g., Claude, Cursor, etc.); you are capable of leveraging these tools to significantly accelerate your output from day one.
• Education: B.S. or Master’s degree in Computer Science, or equivalent work experience.