Top Software Engineer Jobs

Build and maintain end-to-end mobile trading systems for iOS and Android. Ship production-quality, well-tested code, apply blockchain and crypto knowledge, and integrate AI tools to improve engineering workflows. Break down projects, collaborate cross-functionally, conduct and act on code reviews, mentor teammates, and participate in hiring and onboarding. Influence product decisions through data-driven insights and provide domain expertise for mobile trading initiatives.

Design and implement AI-driven optimizations for software development workflows, leveraging LLMs and Agentic AI to enhance productivity and reliability.

Own end-to-end engineering of in-vehicle voice assistant features, driving architecture, integration, validation (HIL/SIL), and release. Collaborate with product, design, systems, audio/acoustics, and external partners to define requirements, manage interfaces, triage defects, and deliver OTA feature improvements across vehicle programs.

The AI Engineer designs, develops, and deploys AI-driven applications for non-data scientists, enhancing decision-making and model accessibility for organizations.

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.

Design, develop, test, and maintain scalable web applications using .NET and Angular. Integrate AI/ML models and services (chatbots, recommendations, NLP), build and consume RESTful APIs, optimize performance and security, participate in code reviews, and ensure quality via testing and CI/CD practices.

Build and own full-stack features for core user journeys, shipping backend APIs, async workflows, and frontend experiences. Contribute to architecture, write well-tested maintainable code, partner with product and design, and proactively address technical debt and performance issues.

Architect and implement a cross-platform design product across client apps, cloud services, and device connectivity. Champion AI-native engineering practices, drive end-to-end architecture and ADRs, ensure security/reliability/observability, own delivery and release health, and mentor engineering leaders while partnering cross-functionally across product, design, firmware, and security.

Lead design and implementation of cloud-native, AI-native, event-driven platforms for fraud and risk. Define architecture, enforce standards, mentor engineers, design low-latency RESTful services, integrate AI/ML features, and ensure scalability, resilience, security, observability, and cost optimization across teams.

Direct AI coding agents to build and ship marketing sites, maintain brand voice and design discipline across five brands, own SEO and information architecture, run competitive research, and review/correct AI-generated code and copy to ensure production-quality outcomes.

Develop, test, deploy, and maintain .NET-centric web applications using C#, Angular 17+, and Azure. Build and consume REST APIs, work with SQL Server, source control, CI/CD pipelines, and collaborate on code reviews, debugging, performance optimization, and third-party integrations.

Lead design, build, and operate backend agentic systems that analyze large-scale time-series telemetry. Own product from customer discovery through shipping. Implement APIs, distributed job execution on Kubernetes, sandboxed code execution, context/memory management, evaluation suites, and observability while integrating frontier models and scaling agent workloads.

Build and operate backend systems for agentic AI that analyze large-scale time-series telemetry. Own product features from customer discovery through deployment: APIs, distributed job execution on Kubernetes, sandboxed code execution, context management, observability, model integration, and evaluation suites.

Develop tools for AI workload profiling and debugging in GPU clusters, collaborating with various teams to enhance performance and efficiency.

The role involves collaborating on AI GPU deployment, optimizing performance, mentoring engineers, and improving user experience on NVIDIA RTX platforms.

The Staff Software Engineer will lead the development of cloud-native AI platforms, optimizing AI workload deployment in Kubernetes environments and collaborating with cross-functional teams.

The Technical Lead will design, build, and modernize IVR and Voice Bot platforms, providing technical ownership and leadership in a hands-on role within the Contact Center Technology department.

As a Software Engineer at Paces, you will build AI automation solutions to expedite power development, working closely with industry experts and taking ownership of projects to enhance scalability and features.

The Technical Lead will oversee software architecture, mentoring teams and leading the design and implementation of AI-augmented enterprise software solutions.

The role involves leading large-scale projects, driving application development, providing architectural guidance, mentoring teams, and ensuring compliance with standards in AI and technology.

The Advisor Lab Automation Software Engineer will design and implement software integrations for lab automation, focusing on AI-driven processes, while providing technical leadership and mentoring.

As a Software Engineer in Frontier AI Infrastructure, you'll design secure systems for the public sector, improve engineering standards, and collaborate with cross-functional teams to meet government requirements. You'll also participate in customer engagements and contribute to the product strategy while ensuring compliance with federal regulations.

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

As a Staff Software Engineer, you will design, build, and operate the Agentic Data Plane (ADP) and cloud services across major cloud providers while leading system architecture and ensuring system reliability and scalability.

Lead design and implementation of Java/Spring middleware and microservices, optimize Oracle/SQL and MongoDB interactions, integrate AI tools into development and CI/CD, mentor engineers, drive architecture, testing, deployment, and production stability, and apply AI for code generation, monitoring, and risk analysis.