Hands-on L3 engineer building and operating high-scale Go-based email delivery systems across AWS and Azure. Focus on distributed systems, IaC with Terraform, observability, and mentoring.
139k – 204k
Remote4+ YOEBackend Engineering
About the role
Responsibilities
Architect and ship reliable, high-velocity features that handle critical traffic with low end-to-end latency. Partner closely with product management and technical leadership to break down complex system requirements into manageable, iterative milestones.
Drive rigorous code reviews and push for maintainable patterns in our Go codebase, ensuring high testing standards (unit, integration, and component testing) are executed across the team.
Manage and enhance cloud configurations across AWS and Azure environments utilizing Infrastructure as Code (Terraform). Ensure deep observability coverage by standardizing metrics, alerts, and distributed tracing across core data pipelines.
Advocate for a clean architectural foundation. Proactively identify technical debt, system bottlenecks, and single points of failure (SPOF), balancing feature delivery with critical platform refactoring.
Foster a collaborative environment by mentoring junior engineers, leading technical sprint planning, and sharing expertise across distributed engineering nodes.
Requirements
4+ years of professional software engineering experience building and operating resilient backend services at scale.
Practical experience leveraging AI-assisted development tools (such as Claude Code) to accelerate code generation, automate testing, and streamline debugging workflows.
Strong, hands-on production experience writing clean, idiomatic, and highly concurrent Go (Golang), Java or Python.
Solid experience deploying and managing production workloads in cloud environments—ideally with deep exposure to AWS core services (such as EC2, S3, Aurora, or DynamoDB) AND Microsoft Azure equivalents (such as Virtual Machines, Blob Storage, Azure SQL, or Cosmos DB).
Proficiency with Terraform for provision-level automation and maintaining environment parity.
Strong theoretical and practical understanding of distributed datastores, caching layers, and asynchronous event streaming (e.g., Kafka or similar queuing ecosystems).
Strong foundational background in computer science fundamentals, data structures, and building self-healing cloud architectures.
Build secure backend systems and tools for AI model inference and Public Sector customers. Own reliability, develop CLIs for deployment/testing, collaborate on integration tests. Requires security clearance and hybrid office presence in SF, NYC, DC, or STL.
138k – 259k
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