Software Engineer (L2) Email

Twilio

13h•$116,960 - $146,200•Remote

About The Position

This position is an engineering role within Twilio Platform Engineering, suited to an engineer who is building hands-on experience with highly available, large-scale distributed systems. Our systems regularly process more than 12 billion emails during peak events like Black Friday, and our throughput requirements continue to scale rapidly. As an L2 engineer, you will help build and operate backend services at scale, working alongside more senior engineers on our dual-cloud infrastructure spanning Amazon Web Services (AWS) and Microsoft Azure. You'll get hands-on with Kubernetes, contribute to Terraform-based infrastructure automation, and write production code to help keep distributed systems healthy under real production load, using modern AI-assisted tooling to move faster and ramp up your skills.

Requirements

1-2+ years of professional software engineering experience, including some exposure to building or operating backend services using Kubernetes.
Familiarity with basic Kubernetes operations (deployments, pods, services) is expected; deep production-scale cluster-upgrade experience is not required.
Practical experience with, or strong desire to learn, AI-assisted development tools (e.g., Claude Code) to help write code, automate testing, and support debugging workflows.
Some exposure to GitOps workflows (e.g., ArgoCD) and CI/CD pipelines (e.g., Harness or an equivalent platform); willingness to learn our specific tooling on the job.
Working knowledge of at least one of Shell, Terraform, YAML, or Go (Golang), with a willingness to build proficiency across the rest.
Some experience with cloud environments, ideally basic exposure to AWS core services (such as EC2, S3, EKS) or their Microsoft Azure equivalents (such as Virtual Machines, Blob Storage, AKS).
General familiarity with networking concepts (VPC/VNet basics) is a plus.
Basic familiarity with Terraform or similar IaC tools.
Foundational understanding of distributed datastores, caching layers, or asynchronous event streaming (e.g., Kafka or similar queuing systems), through coursework, projects, or professional experience.
Solid computer science fundamentals and data structures knowledge, with an eagerness to learn how to build self-healing cloud architectures.

Nice To Haves

Some exposure to containerized infrastructure (Docker, Kubernetes) in coursework, internships, or professional projects.
Curiosity about advanced deployment strategies (canary, blue/green); prior hands-on experience not required.
Interest in policy-as-code tools such as OPA/Gatekeeper.
Interest in OpenTelemetry or distributed tracing concepts.
Any exposure to network topology, proxy layers, or mail transfer agent (MTA) protocols.
Coursework or personal projects involving distributed datastores, caching, or event streaming (e.g., Kafka).
Interest in multi-cloud environments and a desire to build that experience over time.

Responsibilities

Help design, build, and operate services and automations that support Kubernetes clusters at scale, under the guidance of senior engineers.
Work with product management and technical leadership to turn well-scoped tasks into working code.
Participate in code reviews and follow established patterns and testing standards (unit and integration testing) across the team and platform.
Support cloud configurations across AWS and Azure environments using Infrastructure as Code (Terraform).
Help maintain observability coverage, including metrics, alerts, and basic distributed tracing, across core data pipelines.
Build awareness of clean architectural practices.
Flag technical debt, bugs, and small-scale system issues to your team as you encounter them.
Actively seek feedback and mentorship from senior engineers, participate in sprint planning, and share what you learn with peers as you grow into a more senior role.