Build & Release Engineer

Posted 12 Days Ago
Be an Early Applicant
Vancouver, BC
Hybrid
130K-165K Annually
Senior level
Artificial Intelligence • Computer Vision • Machine Learning
The Role
Own and maintain CI/CD for cross-platform C++ and Unreal Engine builds, improve build determinism and performance, manage build agent infrastructure and source control (Perforce/Git), orchestrate automated testing and release engineering, and drive automation to accelerate reliable releases.
Summary Generated by Built In
About the Role

Before an autonomous vehicle navigates a busy intersection, before a robot learns to pick and place in a warehouse, before any Physical AI system is trusted in the real world—it has to prove itself in ours. Parallel Domain builds the platform where the next generation of autonomy and Physical AI is tested, validated, and pushed to its limits in high-fidelity virtual simulations that would be impossible, dangerous, or prohibitively slow to replicate in the real world. Our simulation team is the engine room: they build the simulation core and advanced rendering pipeline that make all of this possible. We’re looking for a Build & Release Engineer to own the infrastructure that keeps this team moving fast. You’ll be the person who ensures that a C++ simulation change compiles cleanly across Linux and Windows, that an Unreal Engine upgrade doesn’t break downstream pipelines, that every release candidate is rigorously validated, and that builds that used to take an hour now take fifteen minutes. This is a high-leverage role where your work directly accelerates how quickly we can ship the platform our customers depend on to make autonomy safe.

Responsibilities

  • Own and maintain all CI/CD pipelines across Jenkins and GitHub Actions, covering C++ compilation (Linux and Windows), Unreal Engine builds, container image builds, automated testing, and release packaging.
  • Make builds explainable end to end. For any artifact, you can answer what inputs produced it, which toolchain was used, what dependencies were pulled, and why. Make the dependency graph and build provenance visible so that anyone on the team can trace a failure to a specific link in the chain.
  • Own dependency hygiene: define what can float versus what must be pinned, and enforce it through CI policy and tooling. Drive build determinism as a first-class property of every pipeline.
  • Drive build performance by profiling compilation hotspots using clang tooling (clang-tidy, clang-scan-deps, -ftime-trace, -ftime-report), identifying the slowest modules and translation units, and systematically eliminating bottlenecks. Apply the same investigative rigor to content cooking, shader compilation, and asset packaging times.
  • Maintain the CMake-based build system that targets Ninja, Visual Studio, and other generators, ensuring consistency across all platforms and build configurations.
  • Manage build agent infrastructure including cloud-based build machines (AMIs, instance selection), Docker build environments, and self-hosted CI runners.
  • Administer source control across Perforce (C++, Unreal Engine project, content assets) and GitHub (SDK, infrastructure-as-code, tooling), including branching strategies, access controls, and cross-system integration.
  • Own the release engineering process: creating and managing release branches, building and validating release candidates, managing versioned build artifacts across S3 and container registries, and coordinating release packaging and promotion.
  • Maintain and expand automated test orchestration across the full test pyramid: unit tests, integration tests, end-to-end tests, performance benchmarks, and Unreal functional tests.
  • Monitor build and pipeline health, triage failures, and drive CI back to green. Implement alerting and dashboarding for build reliability metrics.
  • Default to automation over manual process. If something is done by hand more than once, build tooling to eliminate it.
  • Collaborate with SRE on Kubernetes and workflow orchestration infrastructure, and support Unreal Engine version upgrades and their downstream build pipeline impacts.

Required Qualifications

  • 5+ years in build engineering, release engineering, or DevOps with significant C/C++ cross-platform (Linux and Windows) build system experience.
  • Deep expertise with CMake, including generator support for Ninja and Visual Studio, and experience managing complex dependency graphs in large codebases.
  • Strong hands-on experience with Jenkins (pipeline authoring, multibranch pipelines, agent management) and GitHub Actions (workflow authoring, self-hosted runners, caching, matrix builds).
  • Proficiency with both Perforce (depot administration, workspaces, branching, shelving) and Git/GitHub (branching strategies, multi-repo workflows, large repository management).
  • Hands-on experience with clang tooling for build analysis and optimization: clang-tidy, clang-scan-deps, -ftime-trace, -Rpass, and -ftime-report. You should be able to profile a build, identify the slowest translation units, and trace the root cause of compilation bottlenecks.
  • A track record of improving build provenance and reproducibility: dependency pinning strategies, hermetic builds, and tooling that makes the build graph inspectable and auditable.
  • Solid Docker skills: multi-stage builds, image optimization, registry management, and containerized build environments.
  • Working knowledge of AWS (EC2, S3, ECR, EKS) or equivalent cloud infrastructure for build systems.
  • Experience with artifact management, release packaging workflows, and semantic versioning strategies.
  • Comfortable using modern AI tools and LLM-assisted workflows to accelerate pipeline authoring, refactors, diagnostics, and documentation. You look for ways to amplify yourself with tools.

Preferred Qualifications

  • Experience building and shipping Unreal Engine projects in CI/CD, including build automation, content cooking, and plugin compilation. If you haven’t worked with Unreal specifically, you should have extreme curiosity and the self-direction to dive into an unfamiliar engine or toolchain and become productive quickly.
  • Experience at a simulation, game-engine, or robotics company where builds involve large binary assets, content cooking, and multi-gigabyte artifacts.
  • Familiarity with Python scripting for build automation and tooling, and with gRPC/Protobuf code generation in CI pipelines.
  • Experience migrating pipelines between CI systems or managing hybrid CI environments.

What Makes a Great Candidate
You treat build infrastructure as a product. You get frustrated when a build takes 45 minutes and won’t rest until it’s under 15. You think about developer experience as much as pipeline reliability. You’re comfortable diving into a Jenkinsfile one moment and debugging a CMake module the next. You thrive in an environment where the codebase spans C++, Python, Unreal Blueprints, Docker, and Kubernetes—and where “the build” means everything from compiling a physics simulation to cooking a 3D world into a renderable package.

Top Skills

C++,Cmake,Ninja,Visual Studio,Jenkins,Github Actions,Perforce,Git,Docker,Aws Ec2,Aws S3,Aws Ecr,Aws Eks,Clang Tooling (Clang-Tidy,Clang-Scan-Deps,-Ftime-Trace,-Ftime-Report,-Rpass),Kubernetes,Unreal Engine,Llm/Ai Tools
Am I A Good Fit?
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The Company
HQ: Palo Alto, CA
67 Employees
Year Founded: 2017

What We Do

Training and testing autonomous systems in the real world is a slow, expensive and cumbersome process. Parallel Domain is the smartest way to prepare both your machines and human operators for the real world, while minimizing the time and miles spent there. Connect to the Parallel Domain API and tap into the power of synthetic data to accelerate your autonomous system development.

Parallel Domain works with perception, machine learning, data operations, and simulation teams at autonomous systems companies, from autonomous vehicles to delivery drones. Our platform generates synthetic labeled data sets, simulation worlds, and controllable sensor feeds so they can develop, train, and test their algorithms safely before putting these systems into the real word.

#syntheticdata #autonomy #AI #computervision #AV #ADAS #machinelearning

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