Software Engineer, Abnormal Security

• Strong experience with Python 3.x:
• CLI development (e.g., Click or similar)
• YAML/Jinja2-style templating
• Modern type hints and typing discipline (e.g., typing, dataclasses / attrs, Pydantic-style patterns)
• Testing with pytest or similar
• Solid experience with Go:
• Shared library and service development (gRPC/HTTP)
• CLI patterns (e.g., Cobra/Viper or equivalents)
• Testing with Go testing frameworks (e.g., Ginkgo/Gomega or the standard library)
• Schema design and evolution
• Cross-language client/server generation and integration
• Bazel in a large monorepo:
• BUILD rules and dependency management
• Working with code generation for APIs and clients
• Containers & orchestration:
• Docker image builds
• Kubernetes concepts (Helm-style values, service deployments, readiness/liveness/health checks)
• Cloud infrastructure (AWS preferred):
• Experience with a meaningful subset of: object storage, relational databases (e.g., Postgres), key–value/document stores, search, streaming/ingest services, Kafka, Redis, IAM
• Modern CI systems (e.g., Git-based CI/CD platforms):
• Authoring non-trivial pipelines (matrix builds, reusable workflows, secrets/permissions)
• Infrastructure-as-Code mindset:
• Comfortable working with service manifests (YAML), Terraform/Terragrunt-like patterns, or internal equivalents
• Linting & static analysis:
• Hands-on experience configuring and tuning linting and typing tools (e.g., pylint, ruff, mypy, golangci-lint)
• Experience writing or extending custom lint rules is a strong plus
• Designs scalable developer abstractions
• Has built tools that many engineers depend on, and can point to where those abstractions worked (or didn’t) and why
• Operates across the full platform stack
• Comfortable jumping between Python CLIs, Go libraries, Bazel rules, YAML manifests, CI workflows, and Kubernetes deployments
• Reduces complexity for others
• Measures success by how much simpler and safer life becomes for product engineers and AI agents using the platform
• Thinks in terms of leverage
• Prefers building guardrails, automation, and self-service over manual ops work
• Writes clear documentation
• Treats usage and developer documentation as part of the product surface, not an afterthought
• Collaborates across teams
• Communicates clearly with product teams, infra, SRE, and security; comfortable gathering feedback via Slack, ticketing systems, and design docs and iterating quickly

Desirable

• The Dev Accelerator team builds and operates our internal developer platform: the tools, libraries, and infrastructure that let 100+ engineers design, build, test, and ship products quickly and safely
• Design and evolve the internal developer platform that underpins virtually all backend development
• Own high-leverage projects across CLI tooling, CI/CD, shared libraries, and test infrastructure
• Work across Python, Go, Bazel, Kubernetes, AWS, and CI systems to make our Golden Path fast, reliable, and intuitive
• Shape abstractions and workflows that are AI-native, consumable by both humans and AI agents
• You’ll operate as an IC, leading multi-quarter initiatives and collaborating with product teams, infrastructure, SRE, and Security
• Build and evolve developer CLI tooling
• Extend our primary developer CLI to scaffold new component types and services end-to-end (service manifests, container/build configs, deployment charts, build files, API definitions, starter code, alerts, runbooks)
• Improve environment and credentials tooling to make local development setup fast and reliable
• Own core CI/CD and linting infrastructure
• Design and maintain the backend CI workflow used by backend services
• Evolve linting, formatting, and typing tools to enforce architectural and code-quality guardrails across the monorepo
• Debug and fix CI issues that block engineers, and proactively reduce flakiness and runtime
• Steward shared Go and Python ecosystems
• Own key shared Go libraries (auth, caching, clients, configuration, cryptography, logging, metrics, domain/realm, server, etc.) and their usage across many applications
• Maintain and evolve Python shared libraries and frameworks in our core libraries, gRPC helpers, utilities, and standardized components
• Strengthen test and release safety
• Extend automated canary analysis with new metric types, backtesting, and safer defaults
• Build and improve test automation tooling, bad-test detection dashboards, and dependency-analysis utilities to keep main green and tests reliable
• Contribute to automation that classifies CI failures and summarizes them for engineers (including LLM-assisted workflows)
• Drive platform-level design and abstractions
• Design abstractions that balance simplicity for product engineers with enough power for advanced use cases
• Collaborate with PM/TPM, infrastructure, and product teams to scope and deliver multi-team initiatives (e.g., prompt-to-product workflows, typing and linting initiatives, test automation)