Senior Software Engineer, Everlaw

• You are a builder, not just a maintainer. You prefer writing a plugin, CLI, or automation over manually clicking through a console, and you have a track record of automating away your own toil
• You have 5+ years of software engineering experience with a focus on Release, DevOps, or Platform Engineering in cloud-based systems
• Strong proficiency in Java or a similar statically-typed language, and comfort scripting in Python and/or Bash
• Deep, hands-on experience with build tools such as Gradle, Bazel, or Maven at scale (large codebases, many modules, complex dependency graphs)
• Experience managing cloud infrastructure (AWS preferred) using Terraform or similar IaC tools
• Experience operating modern CI/CD platforms (e.g., GitHub Actions, Harness, GitLab CI, or similar) and improving their performance, reliability, and ergonomics
• Strong fundamentals in data structures, algorithms, and system design, and familiarity with distributed systems and networking concepts
• Excellent communication and collaboration skills, and demonstrated experience leading multi-developer efforts, including planning and technical breakdown
• Someone who values “boring” reliability: you take pride in pipelines that run thousands of times without failure, and you build in error handling, retries, and idempotency by default
• Excited about AI and agents, even if you are not training models yourself. You understand that for AI agents to be effective, the underlying infrastructure must be deterministic, observable, and API-driven, and you are motivated to build that foundation

Desirable

• We are looking for a hands-on Senior Software Engineer to build, optimize, and harden the pipelines, data models, and APIs that make this possible
• This is an execution-heavy, software engineering role, not a “keep the lights on” position maintaining legacy tooling
• You will be writing code, tuning Gradle/Bazel builds, debugging CI flakes, and implementing the specific API endpoints that allow both humans and agents to interact with our infrastructure safely
• You will build the high-performance plumbing that powers our transition to an agent-ready platform
• This is a full-time, on-site position located in Oakland, California with an expected hybrid schedule of 3 days/week in the office and 2 days/week at home
• The Release team in Platform Engineering owns the “path to production” for the entire Everlaw engineering organization. We are responsible for:
• The Build: Managing compilation and packaging for our large JVM monorepo and related services
• The Pipeline: Operating the CI/CD systems that validate and promote changes across FedRAMP and commercial environments
• The Future: Making the release platform “agent ready.” That means refactoring our infrastructure to be deterministic, API-driven, and structurally transparent so AI agents can reason about changes without hallucinating, and can act within well-defined safety guardrails
• You’ll work closely with Product Engineering, Security Engineering, and our emerging AI/Agentic DevEx efforts to make shipping changes to Everlaw faster, safer, and more automatable
• In your role, you'll Modernize and Scale Core CI/CD and Build Performance
• Your first mandate is to make our existing release platform fast, reliable, and observable
• Reduce build and test times: Dive deep into Gradle/Bazel configurations and our Java build graph to improve cache hit rates, parallelism, and resource utilization for our monorepo
• Increase signal quality: Systematically identify and eliminate flaky tests and unstable infrastructure in our CI pipelines so that a “green build” is a highly trustworthy signal
• Automate compliance: Build automations that generate FedRAMP and other audit artifacts from our pipelines (e.g., change logs, approvals, evidence of controls), reducing manual toil while improving our compliance posture
• Measure what matters: Instrument CI/CD and release workflows with metrics and dashboards for latency, reliability, cost, and failure modes, and drive concrete improvements from those insights
• Full AI agent integration is a longer-term goal. As we mature our release platform, you’ll help lay the groundwork for “agent-ready” infrastructure by:
• Improving data hygiene: Gradually shifting logs and build outputs from unstructured text toward structured, traceable formats, making debugging easier for humans now and enabling future automation
• Encouraging API-first operations: When building new tools or refactoring pipelines, leaning toward clear, idempotent APIs instead of ad‑hoc “click‑ops” or one‑off scripts, so we reduce toil today and keep the door open for safe orchestration later
• Strengthening automated guardrails: Supporting efforts to replace purely human-dependent review steps with policy and safety checks in code, speeding up releases now and defining the boundaries future automation must respect
• Improving machine-friendly observability: Helping ensure that build and release failures emit clear, parsable signals instead of opaque “red builds,” enabling better automated triage over time
• Own release infrastructure as code: Use tools like Terraform and Helm to define and evolve the infrastructure that powers our builds and deployments (runners, clusters, queues, controllers, supporting services)
• Maintain and scale environments: Manage configuration drift, health, and scaling of our pre-production and production deployment targets, with a focus on safety and repeatability
• Enable safe, frequent deployments: Help design and roll out deployment strategies (e.g., blue/green, canary, feature-flag-driven rollouts) that balance rapid delivery with reliability across multiple environments, including regulated contexts
• Support ephemeral environments: Design and support PR- or feature-scoped ephemeral environments for safe, isolated validation of changes (including agent-generated changes), building on existing environment primitives
• Participate in on-call: Join an on-call rotation for critical release and platform incidents, and help improve runbooks, automation, and post-incident learnings
• Lead multi-developer efforts: Drive complex projects end-to-end: scoping, technical design, execution, rollout, and post-launch improvements in partnership with your Engineering Manager and peers
• Mentor others: Provide technical mentorship on CI/CD, IaC, and agent-ready infrastructure; review designs and code; and help grow expertise across Platform and Product Engineering
• Partner across teams: Collaborate with Product, Security, SRE, and AI/Agentic DevEx to ensure our release platform meets the needs of both developers and customers