Top Software Engineer Jobs

Own and deliver a product surface end-to-end within PayZen's provider and partner platform. Build reliable, AI-native features in a compliance-regulated environment (HIPAA/PCI-DSS/SOC 2), identify gaps, write clear stakeholder-facing documentation, mentor junior engineers, participate in hiring, and automate shared tooling.

Build and lead architecture for ServiceTitan’s AI-native developer platform, including coding-agent runtimes, orchestration layers, harnesses, build systems, CI/CD, developer portals, safety guardrails, and compliance infrastructure. Deliver production-scale platform projects autonomously, influence engineering direction across teams, anticipate long-term technology needs, establish reusable engineering patterns, and mentor senior engineers.

Develop and maintain Ruby on Rails applications, write and review code, troubleshoot bugs, and collaborate with developers, QA engineers, product managers, and designers. The intern will receive mentorship while contributing to financial technology products and learning about scalable systems, testing, APIs, Agile methods, and consumer finance.

Build and scale secure backend microservices for payments, disbursements, and governance, risk, and compliance workflows. Design distributed systems capable of handling millions of daily requests using Google Cloud and modern infrastructure tools. Collaborate with product, operations, and compliance teams, mentor junior engineers, and improve platform capabilities through analytics and user feedback. The role requires strong software engineering fundamentals, REST API experience, fintech or financial systems knowledge, and familiarity with event-driven and hexagonal architectures.

Build and scale secure backend microservices for payments, disbursements, or governance, risk, and compliance. Design distributed systems handling millions of daily requests, integrate Google Cloud services, implement financial and compliance workflows, and maintain high performance and security. Collaborate with product, operations, and compliance teams, mentor junior engineers, and continuously improve platform capabilities through analytics and user feedback.

Build and scale backend microservices for payments, disbursements, or governance, risk, and compliance systems. Design secure, high-performance distributed infrastructure using Google Cloud and modern engineering practices. Develop REST services, support financial workflows, collaborate across product and compliance teams, mentor junior engineers, and continuously improve platform capabilities. The role requires experience with fintech applications, payment or compliance systems, security, KYC/AML, and scalable web services.

Build and scale backend microservices for payments, disbursements, or governance, risk, and compliance systems. Design secure, high-performance financial infrastructure using Google Cloud and distributed-system technologies. Develop REST services, support transaction processing, onboarding, KYC, and compliance workflows, and collaborate cross-functionally with product, operations, and compliance teams. Mentor junior engineers, improve engineering practices, and iterate on platform capabilities using analytics and user feedback.

The Principal Software Engineer will lead architecture and development efforts for next-generation Data Center products, collaborating with customers and addressing complex technical issues.

The Senior Software Engineer will design and optimize communication libraries for GPU-based computing systems targeting deep learning and HPC, contributing to parallel programming interfaces and system software.

Design and develop server applications for managing NVLink networks, collaborate on new features, and oversee integration testing and QA.

Senior software engineer on Developer Tools working across frontend and backend to design, implement, and ship profiling features for cloud and cluster environments. Collaborate with cross-functional teams, interact with users, and deliver end-to-end product features from prototypes to demos focused on collecting, analyzing, and visualizing performance data.

The role involves architecting and operating NVIDIA's cloud-native attestation platform, developing high-availability services, collaborating with cross-functional teams, and mentoring engineers.

Develop optimization engines for VLSI physical design at NVIDIA, focusing on algorithms in C++ for timing optimization, with significant hardware and software collaboration.

Develop production-grade integrations for NVIDIA Grove across AI frameworks including Dynamo, llm-d, Ray, and PyTorch. Build adapters, plugins, operators, runtime components, reference workflows, and developer tooling. Optimize distributed multi-node and multi-GPU training and inference, improve Kubernetes observability, define APIs, and troubleshoot containers, networking, scheduling, CUDA, and framework behavior. Collaborate with engineering teams and open-source communities to upstream maintainable changes and ensure compatibility across rapidly evolving dependencies.

Principal-level software engineering leader responsible for architecting, building, and operating reliable enterprise AI applications and agent infrastructure. The role spans frontend, backend, distributed services, data flows, deployment, observability, testing, release engineering, security, and incident response. Responsibilities include developing reusable orchestration, memory, evaluation, telemetry, and policy capabilities; operationalizing NVIDIA AI technologies; defining secure agent collaboration architecture; mentoring engineers; and partnering cross-functionally to deliver production-grade AI systems.

The Senior Software Performance Engineer will optimize NVIDIA's autonomous driving solutions, enhance software architecture efficiency, and develop performance-driven product code in C++, collaborating with multiple teams.

The role involves optimizing CUDA kernels for geometric neural networks, building interfaces for PyTorch and JAX, and collaborating with research teams to develop GPU-accelerated software for scientific applications.

Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems.

As a Principal Software Engineer, you'll develop software systems for NVIDIA's rack-scale infrastructure, defining software architecture, collaborating across teams, mentoring engineers, and ensuring high-quality technical decisions in complex environments.

Build and maintain scalable 3D simulation software for digital twins and synthetic data generation. Develop backend services, AI agents, distributed computing solutions, cloud applications, and frontend components. Optimize performance and reliability, collaborate with product and cross-functional teams, participate in code reviews, and guide innovative solutions involving physical AI, computer graphics, and deep learning.

Build and optimize CUDA kernels for molecular dynamics simulations, deliver GPU-accelerated math primitives, integrate them into major simulation engines, and develop CI/CD systems for performance testing across NVIDIA GPUs. Collaborate with applied scientists to productionize algorithms and support external partners. The role requires deep C/C++ and CUDA expertise, high-performance computing experience, familiarity with molecular dynamics, and experience developing scientific software or GPU APIs.

Develop and scale autonomous vehicle simulation platforms supporting training, testing, validation, and debugging across millions of scenarios. Build Real2Sim and Sim2Real domain adaptation workflows, optimize distributed simulation infrastructure, and contribute across computer vision, deep learning, neural rendering, generative AI, and synthetic data systems. Collaborate with researchers, infrastructure engineers, and product teams to transfer technologies into production and open-source projects.

Benchmark and optimize deep learning model inference and training performance on NVIDIA GPUs. Develop tooling for automated benchmarking, analysis, and performance optimization of CUTLASS kernels. Identify gaps between theoretical and realized performance, recommend software or model improvements, and serve as the team’s kernel-performance authority across GPU architecture, deep learning frameworks, and QA teams.

Design and build end-to-end Real2Sim pipelines and neural 3D reconstruction systems that convert multi-sensor data into simulation-ready scene and object assets. Integrate outputs with mapping, localization, and multi-sensor fusion, collaborate with ML researchers, deploy and optimize large-scale data-generation and augmentation pipelines, and validate and monitor production reconstruction and simulation services.

Lead validation of ML datacenter stacks from cluster to rack scale for CSPs: define test strategies, reproduce and triage customer bugs, validate fixes, run perf benchmarks, manage test data and tooling, produce release-readiness reports, and collaborate with internal and partner engineering teams.