Top Software Engineer Jobs

Lead the consolidation of fragmented robotics services into a unified, scalable production platform. Establish architecture, version control, CI/CD, testing, OTA updates, observability, reliability practices, and customer-system integrations. Own production uptime and incident response while mentoring engineers, defining engineering standards, and eventually leading the software team.

This 12-week, in-person technology internship offers hands-on experience across software and cloud engineering, data science, analytics, AI, cybersecurity, project management, and UI/UX. Interns collaborate with experienced technologists, contribute to healthcare technology projects, attend professional development activities, and may join teams focused on digital products, enterprise data, AI, information protection, insurance technology, or enterprise architecture.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

The Staff Software Engineer will lead the architecture and design for AI workload orchestration on Kubernetes, mentoring engineers and driving technical initiatives across teams.

Build and lead development of Klaviyo's conversational AI platform: native chat surface, agent orchestrator, and agentic UI. Design scalable, reliable systems, ship high-quality code, mentor engineers, drive technical decisions, and improve AI-powered customer experiences.

Lead design and delivery of enterprise integrations, automation, and AI-driven workflows across SaaS platforms. Architect scalable APIs, middleware, and conversational self-service; partner with Security, Infrastructure, and Product to reduce operational toil and enable reliable, extensible enterprise platform capabilities.

Design, build, test, deploy, and maintain cloud-based web applications and microservices. Ensure performance, reliability, and code quality while collaborating on new features, debugging, and optimizing systems. Use AI development tools daily, contribute to infrastructure as code, and promote maintainable architecture and documentation.

Build and ship scalable, performant AI-powered Copilot web experiences for millions of users. Design reusable frontend systems, deploy frontend infrastructure, and collaborate with AI researchers, product managers, and designers. The role emphasizes user-centric product development, safety, reliability, rapid iteration, and high-quality execution in a collaborative environment.

Lead and remain hands-on building an AI-first developer portal and secure external API platform. Define architecture for agent-ready workflows, authentication/credential flows, contract-first APIs, resiliency, observability, and AI-enabled support. Drive cross-functional delivery, coach engineers, and ensure operational controls, auditability, and production readiness for integrations.

Develop and manage enterprise APIs, microservices, full-stack applications, and integrations using C#/.NET and Azure. Design and govern APIs through Azure API Management, build cloud data pipelines, implement CI/CD with Azure DevOps and Terraform, and integrate enterprise systems, messaging platforms, and data warehouses. Apply API security, observability, and AI-assisted development practices while providing production support. Collaborate with distributed teams, mentor developers, lead architecture discussions, and own complex integration solutions end to end.

Senior software systems engineer responsible for high-level design and oversight of software, hardware, and firmware systems. Lead Agile development, ensure quality and security standards, mentor engineers, manage multiple projects, support procurement, perform technical reviews, generate performance reports, and integrate emerging technologies into defense test and training environments.

Build and maintain backend services, APIs, and integration layers for a modular ecommerce platform. Integrate personalization, semantic and LLM search, DAM, PIM, SAP/HANA, ERP, analytics, and customer data systems. Use AI coding agents throughout development while validating code quality, security, performance, and reliability. Design scalable APIs, automated testing, observability, and reusable architecture while collaborating with internal teams, vendors, and implementation partners.

The Lead Full Stack Software Engineer will oversee the development of AI-assisted digital platforms, ensuring technical excellence and mentoring engineers, while integrating modern front-end tech with back-end systems to enhance guest experiences.

Leads enterprise software architecture, technical strategy, and roadmap execution across multiple domains. Designs scalable, reliable systems and platforms using modern programming languages, cloud services, microservices, databases, containers, and DevOps practices. Partners with product and engineering teams, mentors technical staff, influences executives, improves engineering processes, evaluates performance and costs, and drives continuous learning. The role requires extensive software development and architecture experience, strong cloud and Azure expertise, and the ability to transfer research into production.

Develop and sustain cloud software and distributed systems supporting cyber intelligence and AI/ML capabilities. Responsibilities include requirements analysis, Java software development, cloud deployment, integration, testing, RESTful services, analytics, Hadoop ecosystems, Linux systems, and technical documentation. The role requires AWS expertise, Kubernetes, infrastructure as code, CI/CD, microservices, large-scale data processing, and active TS/SCI clearance with polygraph.

Develop and sustain cloud software supporting cyber intelligence and AI/ML capabilities on large-scale compute clusters and AWS infrastructure. Responsibilities include requirements analysis, software development, integration, testing, validation, deployment, maintenance, monitoring, and issue resolution. The role uses distributed NoSQL technologies, big-data frameworks, cloud services, AI/ML algorithms, LLMs, RAG, and agentic workflows to support national security missions.

Develop and maintain cloud software supporting AI/ML and national security missions. Responsibilities include requirements analysis, software development, AWS cloud integration, distributed systems engineering, microservices, testing, troubleshooting, and sustainment. The role uses Java, Linux, Kubernetes, infrastructure-as-code, CI/CD, big-data technologies, RESTful services, and AI/ML frameworks including LLMs and RAG. An active TS/SCI clearance with polygraph is required.

Develop, integrate, test, and sustain cloud software and AI/ML capabilities for national security missions. Responsibilities include AWS architecture, Java-based distributed systems, RESTful services, containerized microservices, Kubernetes, infrastructure as code, CI/CD, Linux scripting, big-data technologies, analytics, LLMs, RAG, and agentic workflows. The role also involves requirements analysis, technical documentation, software integration, testing, issue resolution, and designing solutions using distributed computation and cloud-scale data technologies.

Develop and integrate cloud software supporting cyber intelligence and AI/ML capabilities on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java development, RESTful services, distributed systems, cloud deployment, DevOps, container orchestration, testing, integration, Linux scripting, and troubleshooting. The role also involves big-data technologies, Hadoop ecosystems, LLMs, RAG, analytics, and secure software engineering for national security missions.

Develop and sustain cloud software supporting cyber intelligence and AI/ML capabilities on large-scale compute clusters and AWS infrastructure. Responsibilities include requirements analysis, software development, integration, testing, validation, deployment, enhancement, monitoring, and issue resolution. The role uses distributed NoSQL and big-data technologies, cloud architecture, AI/ML tools, microservices, containers, and infrastructure-as-code. Candidates must have at least two years of relevant software engineering experience and an active TS/SCI clearance with polygraph.

Lead the transformation of Java full-stack engineering teams to AI-native development. Define strategy, tooling, workflows, governance, quality gates, and adoption roadmaps for AI agents across the SDLC. Build an AI engineering center of excellence, train developers, integrate coding and testing assistants with CI/CD and DevSecOps, establish security and IP controls, measure outcomes, and scale practices across client engagements.

Build the enterprise platform for an AI creative product, including workspaces, roles and permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services and APIs for multi-tenant usage patterns alongside polished React/Next.js administration and billing experiences. Collaborate with founders, sales, and customers to convert requirements into production features while taking increasing ownership of enterprise platform surfaces.

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.

Own customer integrations for AI agent evaluations from scoping through delivery. Read API documentation, manage credentials, build custom integrations, run evaluations, assess AIUC-1 compliance, communicate technical results, and surface failure modes. Collaborate with customers, sales, delivery, standards, and core engineering teams while turning recurring field solutions into reusable product capabilities.

Senior individual-contributor owning cost and AI-enablement for a petabyte-scale analytics platform. Build and operate data warehouse, ingestion pipeline, and Airflow; deliver cost-attribution, forecast-driven autoscaling, and production Gen AI (NLP-to-SQL/RAG) systems. Hands-on coding (~70%) plus technical coordination and on-call production support.