Fullstack Engineer (AI)

Location: Hybrid, Palo Alto HQ, United States

Salary: $180K–$220K per year; final compensation depends on experience and location.

Company

hirify.global combines a physics foundation model with GPU-native solvers to deliver fast and accurate simulations for complex physical systems.

What you will do

• Design, implement, and operate Python microservices and gRPC APIs exposing native C++ engines and simulation or inference pipelines.
• Build customer-facing and internal React applications, including UI fixes, pages, and controls.
• Implement end-to-end application logic covering validation, job orchestration, retries, idempotency, transactional correctness, and customer SDKs or APIs.
• Design and operate distributed systems with job partitioning, backpressure, observability, and autoscaling for native compute workloads.
• Build CI/CD pipelines and automated unit, integration, and end-to-end tests across backend, frontend, and native components.
• Participate in on-call rotations, incident response, post-mortems, operational documentation, and collaboration with product, QA, infrastructure, and customer success.

Requirements

• 5+ years of professional software engineering experience building backend or full-stack systems.
• Strong Python service development experience and experience building or consuming gRPC and protobuf APIs.
• Practical PostgreSQL experience, including schema design, safe migrations, query tuning, indexing, and production optimization.
• Experience with React or an equivalent modern frontend framework, TypeScript or JavaScript, HTML, and CSS.
• Knowledge of concurrency and multithreaded programming, including concurrency across language boundaries.
• Experience working in large codebases with testing, CI/CD, code review, documentation, and end-to-end ownership of customer-facing features.

Nice to have

• Experience exposing native C++ functionality to Python using pybind11 or CFFI.
• Experience with MPI, task queues, job schedulers, Kubernetes, Slurm, or HPC schedulers.
• GPU acceleration experience with CUDA or ROCm, or experience integrating GPU-accelerated C++ libraries.
• Knowledge of binary serialization, zero-copy techniques, high-performance I/O, observability, authentication, and Linux internals.
• Familiarity with EDA or layout file formats such as OAS, GDS, ECXML, STL, or STEP.

Culture & Benefits

• Pragmatic engineering focused on maintainable, well-tested solutions.
• Emphasis on systems curiosity, clear code reviews, documentation, mentorship, and operational quality.
• Competitive salary and equity.
• Health benefits, flexible time off, and remote-friendly policies.