Top Senior Software Engineer Jobs in Greensboro, NC

Leads the development and deployment of data solutions using Palantir Foundry and AIP. Manages engineering teams, coaches team members, oversees project planning and execution, analyzes system interactions, manages client relationships, and drives innovation. The role applies software engineering, data engineering, analytics, and AI/ML techniques to deliver scalable client solutions while maintaining technical and professional standards.

Leads the development and deployment of software and data solutions using Palantir Foundry and AI/ML technologies. Responsibilities include data engineering, analytics, system improvement, client account management, project ownership, team leadership, coaching, stakeholder engagement, and continuous improvement. The role requires building scalable applications with large datasets and delivering customer-focused solutions.

Build and operate high-throughput backend services for AI agents, calendar, scheduling, integrations, real-time data pipelines, and APIs. Design platform infrastructure, event-driven systems, and client-server protocols using Go, PostgreSQL, Kubernetes, and cloud platforms. Collaborate with AI, product, and frontend teams, improve reliability through testing and infrastructure as code, and mentor junior engineers.

The Founding Engineer will lead the development of Sailor Health's AI-powered platform, building systems for patient care and mentor the engineering team.

Build the core AI platform for an AI-native trading experience. Develop a high-performance Rust backend supporting streaming responses, low-latency tool execution, caching, and model orchestration. Design secure, observable APIs and runtime components with authentication, authorization, rate limiting, auditing, tracing, retries, and fallbacks. Build safe trading action infrastructure with deterministic previews, confirmations, idempotency, and audit logs while partnering with product and frontend teams.

Own and improve Hex’s cloud infrastructure, CI/CD, observability, databases, security, cost management, and single-tenant deployment systems. The role involves selecting and delivering infrastructure projects, operating Kubernetes and AWS environments, scaling PostgreSQL, implementing infrastructure as code, and building customer-facing platform capabilities. Engineers are expected to handle on-call responsibilities, write application code when needed, and independently turn ambiguous infrastructure problems into shippable solutions.

Build and ship backend features end-to-end using Ruby on Rails and SQL. Lead complex technical projects, solve architecture challenges, establish standards, conduct meaningful code reviews, resolve high-risk bugs, document systems, collaborate across engineering teams, and mentor junior engineers.

Own QA strategy and release quality for POS, back-office, and payments products. Build automated unit, integration, API, contract, and end-to-end tests; integrate testing into GitHub Actions; validate hardware, offline modes, payment flows, and upgrades; establish release gates and test environments; monitor quality metrics; reproduce merchant issues; and coach engineers on testable design and quality practices.

Design, build, deploy, and maintain resilient, scalable software for Toast Delivery Services. Develop real-time delivery tracking, driver matching, pricing, refunds, and payment-related systems. Solve distributed-systems and scaling challenges, integrate with partner APIs, uphold production reliability, promote strong engineering practices, and mentor teammates.

Own the architecture and technical direction for provider-sourced client products, including lead management, caseload migration, AI-powered inquiry workflows, and provider marketing tools. Partner cross-functionally with product, design, data, sales, customer experience, and pricing teams. Build reliable user-facing systems, guide technical decisions across teams, measure product impact through experimentation, and influence teams without direct authority.

Architect and operate Affirm’s large-scale Amazon EKS compute platform, including cluster lifecycle, node management, autoscaling, shared components, infrastructure automation, workload safety policies, observability, cost and capacity optimization, and self-service workflows. The role drives technical strategy, mentors engineers, partners cross-functionally, and participates in on-call incident response.

Build and ship a full-stack data collection and search platform for defense and intelligence users. Develop frontend, backend, data ingestion, storage, indexing, APIs, and agentic AI capabilities using TypeScript, React, Tailwind, Node.js, PostgreSQL, and AWS. Partner with mission owners, customers, designers, and engineers to translate intelligence workflows into intuitive, mission-ready products supporting information analysis and visualization.

Build and optimize automated release engineering systems, including CI/CD pipelines, build and deployment tooling, and AWS cloud infrastructure. Ensure software delivery quality, security, compliance, and reliability. Lead complex projects, participate in on-call support, mentor teammates, and promote technical excellence. The role uses Go, Java/Kotlin, TypeScript, GitHub Actions, PostgreSQL, DynamoDB, Backstage, AWS, and AI development tools.

Build and optimize growth systems that increase patient bookings and engagement. Design experiments across messaging, outreach, and in-product booking flows; develop backend systems for experimentation and activation; monitor funnel metrics; analyze drop-offs; prioritize growth opportunities; and collaborate with product, design, data, and operations teams. The role emphasizes rapid experimentation, product-led growth, and measurable improvements in activation, conversion, retention, and booking.

Lead the architecture and technical strategy for Affirm’s high-volume observability platform. Design telemetry pipelines and sampling strategies, improve reliability and cost efficiency, integrate observability into AI-assisted development, and drive platform adoption across engineering teams. Remain hands-on while mentoring six engineers, leading cross-functional initiatives, establishing engineering standards, and overseeing monitoring, alerting, on-call operations, and system availability.

Staff Software Engineer responsible for leading design and delivery of large-scale order platform capabilities spanning cloud and point-of-sale systems. The role drives architecture, performance, reliability, API design, code quality, incident response, and technical roadmap alignment. It also requires cross-team collaboration, domain expertise in order processing and synchronization, mentoring engineers, and using AI-assisted development tools to improve productivity.

Drives performance engineering and scalability across software systems by identifying bottlenecks, optimizing code, queries, databases, and architecture, and implementing fixes. Builds performance frameworks, data-generation tools, benchmarks, and CI/CD automation using k6, JavaScript, Grafana, and InfluxDB. Establishes performance standards, investigates distributed systems and cloud environments, documents architectural decisions, and collaborates with engineering teams to improve throughput, latency, reliability, and efficiency.

Lead frontend technical strategy for Affirm’s checkout decision orchestration systems. Design and architect scalable web applications, guide major technical initiatives, improve reliability and operational processes, establish engineering quality standards, collaborate with product, design, and analytics, and mentor engineers. The role focuses on building fast, clear, and reliable checkout experiences using modern declarative UI frameworks.

Design and maintain automated testing frameworks for cloud-scale distributed systems. Build performance, load, stress, integration, API, end-to-end, chaos, security, and infrastructure tests. Integrate continuous testing into CI/CD pipelines, analyze observability data, validate Kubernetes and microservices environments, and collaborate with Engineering and SRE teams to improve reliability. The role also participates in on-call rotations and helps establish QA strategy and standards across GPU infrastructure, serverless endpoints, storage, billing, and event-driven systems.

Build and operate production backend services supporting Supabase AI products, including the MCP server. Responsibilities include service architecture, deployments, scaling, authentication and authorization, observability, reliability targets, on-call incident response, rate limiting, capacity management, and API evolution. The role requires strong TypeScript or Go skills, production backend experience, distributed-systems debugging, and collaboration with Platform and SRE teams in a fully remote environment.

Develop and lead production software-defined networking for NVIDIA’s global GPU cloud infrastructure. Design multi-tenant control and data planes using Open vSwitch, OVN, OpenFlow, Kubernetes, C, and Go. Build networking services, plugins, automation, testing, observability, and reliability improvements. Lead architecture and code reviews, mentor engineers, support on-call operations, and resolve complex production incidents through diagnostics and source-level debugging.

Design, develop, verify, and maintain embedded system software and kernel drivers for NVIDIA Tegra ARM-based SoCs. Responsibilities include pre-silicon modeling, silicon bring-up, core OS enablement, hardware and software collaboration, unit testing, documentation, and system-level debugging. The engineer will also influence hardware architecture through design specifications and support next-generation SoC platforms.

Develop and maintain graphics system software, user-mode drivers, platform code, APIs, and SDKs across GPU architectures and operating systems. Ensure backward and forward compatibility across driver releases, collaborate on graphics and deep learning technologies, and support next-generation GPU design, development, and validation.

Lead performance practices for large-scale AI systems, enhance datacenter products, and resolve complex performance issues through collaboration and technical expertise.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.