Senior Software Engineer - Dev Accelerator

Abnormal

About The Position

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. We own: Developer CLI tooling – a “Prompt-to-Product” style CLI that scaffolds services end-to-end, environment/credentials tooling, and a wide range of internal developer scripts. Monorepo build, lint, and CI infrastructure, including our core backend CI workflow, Bazel integration, and a custom linting framework and rule set used across the codebase. Go ecosystem stewardship for a large suite of shared libraries and applications under our main Go module. Python shared libraries & frameworks for core business logic, gRPC helpers, utilities, and standardized component libraries (datastores, messaging, web, etc.). Engineering effectiveness & test infrastructure, including automated canary analysis, test data and coverage tooling, bad test dashboards, dependency analysis, and “broken main” automation. Our goal is to make the easy path the right path for product teams and AI agents building on the platform. As a Senior Software Engineer, Dev Accelerator, you will: 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 a senior IC, leading multi-quarter initiatives and collaborating with product teams, infrastructure, SRE, and Security.

Requirements

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).
Protobuf/gRPC:
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.
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.

Nice To Haves

Monorepo experience
Worked in a large, shared codebase with complex dependency graphs and shared frameworks.
Familiar with dependency graph analysis and strategies to keep builds/tests fast.
Developer experience (DX) tooling
Built or maintained CLI tools, scaffolding systems, or internal frameworks used by other engineers.
Thoughtful about ergonomics, documentation, and guardrails.
Testing & progressive delivery
Exposure to canary analysis / progressive rollout systems (e.g., Prometheus/PromQL, Grafana, automated deployment checks).
Experience with test data management, integration/E2E test infrastructure, or bad-test detection.
Messaging & streaming
Experience with Kafka (topic design, producers/consumers, observability, error handling).
LLM/AI integration
Experience or strong interest in using LLMs to improve developer workflows (e.g., failure summarization, smart code generation, AI-native CLIs).

Responsibilities

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).