Top Software Engineer Jobs

Develop and maintain full-stack Java applications using Java EE, RESTful microservices, Oracle, Angular, TypeScript, and Node.js. Use AI coding assistants for code generation, debugging, optimization, and prompt-driven development while validating output for accuracy, performance, and security. Apply JVM performance profiling, software engineering best practices, and potentially CI/CD, DevOps, Docker, Unix scripting, caching, and SAML technologies. The role requires four days onsite weekly in Lansing or Farmington Hills, Michigan.

Develop immersive augmented and virtual reality experiences using Unity and Unreal Engine. Build custom software connecting AR/VR applications with advanced analytics and AI, collaborate with designers and data scientists on quantitative visualizations, and create technical documentation and design artifacts. The role requires solution planning, cross-functional collaboration, and development aligned with project objectives.

Supports the CTO with technology research, AWS and AI exploration, backend development, cloud-native prototypes, REST API experiments, system design, technical documentation, and architecture planning. The intern will build proof-of-concept solutions using C#, Python, .NET, AWS services, and machine learning technologies while evaluating vendors and emerging tools.

The Software Engineer - AI Systems will design and implement systems to coordinate LLMs, build testable software stacks, conduct research, and collaborate with team members to create AI-powered security solutions.

Set technical direction for an AI-native software engineering team building security workflow tools. Lead complex architectural decisions, guide engineers, review designs and code, and collaborate with technical leaders across teams. The role requires extensive hands-on software engineering expertise, strong architectural judgment, mentoring ability, and experience making decisions for scalable systems. Preferred experience includes security tooling, AI agent APIs, MCP servers, and AI-native engineering practices.

Debug, profile, and optimize AI cluster networking and GPU performance across Linux kernels, PCIe, SmartNICs, RDMA/RoCEv2, NCCL, and application communication. Investigate boot, driver, latency, throughput, congestion, and hardware trace issues; analyze packets, logs, profiles, and observability data; and collaborate with hardware and software teams to remove end-to-end bottlenecks.

Own the architecture and technical direction of a heterogeneous AI SoC runtime spanning sensor ingest, preprocessing, inference, postprocessing, and application delivery. Define execution, memory, synchronization, driver, firmware, compiler-runtime, observability, resilience, and validation architectures. Lead cross-functional engineers while contributing hands-on to production systems software, performance optimization, APIs, and low-level interfaces for robotics and edge AI workloads.

Leads the architecture and development of customer-facing SDKs, APIs, CLI tools, examples, documentation, developer workflows, and portal integrations for an AI SoC platform. Partners across AI, multimedia, robotics, tools, release, and SQA teams to deliver reliable installation, deployment, compatibility, and release experiences. The role also hires, mentors, and leads engineers focused on developer tools, documentation systems, APIs, and sample applications.

Define and build the software architecture underlying Velaura’s Physical AI platform, including SDKs, runtimes, drivers, firmware, compilers, developer tools, and workload orchestration. Lead hardware/software co-design, performance optimization, profiling, and integration with ROS2, DDS, robotics, drones, and autonomous systems. Establish engineering processes and help develop a high-performing platform software team enabling efficient AI deployment across heterogeneous computing systems.

Build and maintain backend services and APIs powering LangSmith’s observability and evaluation platform. Responsibilities include architectural design, storage and query optimization, reliability engineering, testing, monitoring, alerting, production troubleshooting, root-cause analysis, technical documentation, and cross-functional feature delivery. The role focuses on high-throughput, mission-critical AI platform systems.

Lead architecture and implementation of LangSmith platform features across Go, Python, and TypeScript. Collaborate with product and design teams, mentor engineers, drive project timelines, and deliver clean, tested software. Build and scale APIs and data-intensive applications using backend and frontend technologies, PostgreSQL, and Redis while engaging with enterprise customers and internal stakeholders.

Build and operate secure, scalable AI compute platform services, including backend APIs, asynchronous workflows, Kubernetes controllers, and multi-tenant workload capabilities. The role focuses on distributed training and inference, platform reliability, observability, developer tooling, and infrastructure simplification. Responsibilities include collaborating across engineering teams, improving scalability and developer productivity, and providing technical leadership for production AI platform capabilities.

Design and build secure, scalable platform services for distributed AI training and inference. Develop backend APIs, Kubernetes controllers, orchestration systems, asynchronous workflows, multi-tenant access controls, and developer tools. Improve reliability, observability, scalability, and engineering productivity while partnering with infrastructure and AI teams. The role also provides technical leadership, mentoring, and cross-functional collaboration throughout platform development and production delivery.

Designs and develops highly available cloud services for AI inference workloads. Responsibilities include building Kubernetes controllers and platform capabilities for deployment, scheduling, scaling, recovery, upgrades, observability, and lifecycle management. The role leads production readiness reviews, resolves complex infrastructure issues, improves reliability and performance, drives architecture and design reviews, mentors engineers, and influences technical direction across teams.

Lead an agile engineering team to design, develop, test, and operate secure, scalable production software. Provide technical guidance, influence product and architecture decisions, deliver high-quality code, and promote firmwide engineering practices and modern cloud-native technologies.

Leads backend architecture and technical strategy for autonomous vehicle and customer support systems. Designs scalable integrations across Fleet, Uber for Business, Direct, and platform teams; develops proactive trip-lifecycle support, Agentic AI capabilities, reliability, and end-to-end testing frameworks. Drives cross-functional technical alignment and mentors senior engineers toward Staff-level impact.

Vice President of Engineering will lead engineering strategy, organization design, hiring, delivery, architecture, infrastructure, reliability, security, compliance, and AI initiatives. The role partners with executive leadership to scale MediCircle’s medication redistribution platform nationally, establish engineering operating standards, manage technical risk and investment, and build a high-performing engineering organization capable of supporting complex pharmacy operations, patient workflows, integrations, and regulatory requirements.

Design, implement, test, and ship secure, high-performance C++ features for Microsoft Edge, focusing on enterprise security, Data Loss Prevention, and Copilot integrations. Lead architecture across browser, cloud, identity, compliance, and management systems; collaborate cross-functionally to deliver scalable customer solutions. Mentor engineers, influence technical strategy, and improve product quality through telemetry and customer feedback.

Lead the architecture and modernization of Citi’s global XVA valuation, risk, and stress-testing platforms. Design scalable distributed systems using Java, Python, cloud infrastructure, microservices, Kafka, and polyglot persistence. Drive Agentic AI, LLM-enabled software engineering, legacy modernization, MLOps, and model governance. Partner with quants, trading desks, and risk officers to deliver regulatory-compliant technology. Lead geographically distributed engineering teams, Agile programs, migration initiatives, resiliency, cybersecurity, and production governance.

Build and productionize customer-facing data and AI solutions on the Databricks Platform. Own architecture, design, implementation, deployment, and integration of scalable data pipelines, machine learning models, and applications. Guide enterprise customers, manage technical delivery, train stakeholders, resolve implementation issues, and contribute reusable frameworks and product feedback. The role requires hands-on engineering, customer immersion, cross-functional collaboration, and travel to customers approximately 20% of the time.

Design, build, and operate Docker’s enterprise AI agent platform using Go and Kubernetes. Responsibilities include cloud control planes, multi-cloud infrastructure, security and network boundaries, reproducible software supply chains, production ownership, on-call operations, SLOs, incident response, distributed systems design, and technical leadership. The role also includes mentoring engineers and collaborating across runtime, identity, developer experience, and observability teams.

Build and own AI-assisted development infrastructure, including autonomous cloud development environments, MCP integrations, agent documentation, internal tooling, and enablement programs. Improve how engineering teams use AI coding agents across the organization, drive cross-team adoption, and stay current with AI productivity trends. The role requires strong software engineering, developer tooling, cloud infrastructure, CI/CD, and application development experience.

Optimize software workloads across datacenter and agentic AI applications on RISC-V platforms. Responsibilities include profiling applications and runtimes, identifying bottlenecks, tuning compilers and runtimes, analyzing memory and concurrency behavior, leveraging vector, matrix, and custom ISA capabilities, and developing AI-assisted optimization workflows. The role collaborates across software, compiler, hardware, and performance modeling teams to improve throughput, latency, efficiency, and future CPU architecture.

Design and build NVIDIA’s enterprise AI agent platform, including agent blueprints, runtime safety and policy enforcement, multi-agent orchestration, credential brokering, checkpointing, observability, evaluation, and self-improvement loops. Deploy reliable long-running services at scale, integrate enterprise systems, support secure execution, and participate in on-call operations. The role requires extensive distributed systems or infrastructure experience and hands-on agent development.

Designs, develops, tests, deploys, and supports robotic process automation workflows and components. Collaborates with business and technical stakeholders to translate requirements into solutions, integrate systems such as SAP, troubleshoot production issues, document processes, train users, and ensure quality, governance, security, and performance. The role also monitors automation impact, supports deployments and on-call operations, and contributes to cross-functional workflow automation initiatives.