Top Senior Software Engineer Jobs

Develops, enhances, and maintains COBOL mainframe applications using DB2 and JCL. Supports ACH payment processing, NACHA compliance, batch operations, system testing, performance monitoring, troubleshooting, and production issue resolution. The role designs and deploys application enhancements, improves system efficiency, manages risk and change controls, collaborates with technical and business teams, and mentors junior engineers. This is an onsite position near Birmingham, Charlotte, or Atlanta.

Design and implement logistics optimization algorithms, develop predictive models, and build simulations for patient scheduling and routing in healthcare.

The Senior Software Engineer will explore AI solutions in healthcare, having experience in full-stack/backend development and startup culture.

As a Senior Software Engineer, you will design and build backend services and APIs for healthcare delivery, ensuring system reliability and integrating medical devices while leading projects and mentoring engineers.

As a Senior Software Engineer at Whatnot, you'll build AI tooling for internal use, developing workflows and infrastructure to enhance software delivery. You'll collaborate across teams to gather feedback and prioritize features in a rapidly evolving landscape.

Develop and maintain C++ systems for Teamfight Tactics on iOS and Android using Unreal Engine. Diagnose cross-platform, engine, and native mobile issues; optimize performance, memory, stability, and reliability; and influence architecture, engineering practices, tooling, testing, and release processes. Collaborate with multidisciplinary teams, provide technical leadership, mentor engineers, and participate in on-call support.

Develop and optimize complex C++ software and algorithms for EO/IR defense systems. Analyze designs, identify flaws, support requirements through testing and integration, and collaborate with systems, hardware, and test engineers. Provide technical leadership, evaluate emerging technologies, improve development processes, and serve as a subject matter expert in algorithm design for electro-optical and infrared applications.

Build and ship end-to-end features for an AI-first customer support product. Work with coding agents, design UI/UX and data models, own features from idea to production, and collaborate on tooling and feedback systems to make agent-driven development reliable and shippable.

Lead architecture and hands-on development of a self-service infrastructure orchestration platform for deploying services across clouds and regions. Design durable distributed workflows with dependency management, approval gates, safe retries, recovery, security, telemetry, and auditability. Apply AI-assisted engineering with human oversight, mentor engineers, lead cross-team reviews, and partner with Azure and Microsoft 365 teams to improve buildout efficiency and reliability.

Designs, implements, and leads large-scale distributed systems and foundational AI infrastructure. Responsibilities include technical strategy, architecture, observability, security, testing, production automation, incident resolution, open-source collaboration, cross-team influence, mentoring, and improving infrastructure for AI workloads such as model inference.

Design, develop, test, document, and maintain scalable big data solutions. Build APIs, evaluate technologies, translate requirements into solution designs, estimate development efforts, and collaborate with engineering, QA, architecture, and management teams. Provide production support, participate in prototypes and code reviews, document solutions, and continuously develop technical skills.

Leads the design, development, testing, and optimization of large-scale data engineering solutions. Responsibilities include building Python and PySpark ETL pipelines, orchestrating workflows, developing AWS cloud-native services, managing data lakes and Snowflake environments, and implementing testing, CI/CD, and secure engineering practices. The role also promotes responsible AI-assisted development, mentors engineers, participates in code reviews, and drives technical delivery initiatives.

Own application-layer reliability for AI-powered features by defining SLI/SLO frameworks, building observability dashboards, analyzing usage trends, and developing LangGraph agents for diagnostics and remediation. Create agent evaluation harnesses, write complex BigQuery SQL, develop Python automation, support safe deployments, and lead incident response and blameless postmortems. Partner with application, data, and infrastructure engineering teams to improve reliability, monitoring, and user experience.

Staff Software Engineer leading architecture, hands-on development, and delivery of reliable frontend, backend, API, data, and production systems across multiple teams. The role drives multi-quarter initiatives, AI-enabled engineering practices, system scalability, security, observability, incident response, technical standards, mentorship, and alignment between technical investments and product outcomes.

Lead architecture and implementation of Together AI’s global GPU cloud infrastructure. Own GPU and network virtualization, in-data-center IaaS, distributed scheduling and management planes, fault-tolerant automation, and customer-facing production systems. Set technical direction across teams, mentor engineers, establish engineering standards, and build scalable services spanning Kubernetes, compute, storage, networking, and GPU infrastructure.

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.

Develop and support Kotlin APIs and high-volume distributed services for audience targeting and machine learning products. Work with Rust, PySpark, Kafka, relational databases, and hundreds of terabytes of daily data. Build reliable systems at scale, optimize existing products, collaborate with product and project leaders, and contribute to engineering culture. The role requires strong JVM-language development, SQL and database expertise, microservices experience, cloud infrastructure knowledge, and effective use of AI coding tools.

Design, implement, and deploy scalable ad-serving, measurement, and targeting systems. Optimize big data applications for performance and cost. Own projects end-to-end, mentor junior engineers, drive technical design and best practices, and collaborate cross-functionally and with global engineering teams to enhance targeting and measurement integrations.

Build and operate end-to-end consumer-scale features across backend services, APIs, iOS, and Android for Life360’s Aging in Place segment. Use AI tools and agentic workflows extensively, establish AI-native engineering practices, contribute to architecture and code reviews, participate in on-call response, mentor teammates, and ensure performance, reliability, accessibility, and member impact across owned features.

Design and maintain large-scale backend services that deliver configurations and features to autonomous vehicle fleets. Build commercialization tools, robust fleet rollout processes, and safe feature launches using evaluation, A/B testing, and gradual deployments. Collaborate with Product, Operations, Data Science, and engineering teams to ensure system safety, reliability, and effective cross-functional execution.

Own and deliver polished, accessible, high-performance frontend experiences using React and TypeScript. Set frontend technical standards, mentor engineers, use AI-assisted development tools, and contribute to product roadmaps. Build backend services and APIs in Go as needed, collaborate with stakeholders, document user-facing products, and help shape engineering culture and quality.

Build and operate automation, tooling, and services for large-scale GPU clusters across cloud and on-premises environments. Develop provisioning, validation, upgrades, monitoring, repair, GitOps, and lifecycle workflows. Improve Day 0–Day 2 operations, reduce manual intervention, troubleshoot distributed systems, and participate in on-call and incident response while partnering across infrastructure teams.

Leads architecture and development of NVIDIA’s network visibility platform, integrating topology, configuration, telemetry, active measurement, change intelligence, and self-service tools. Builds authoritative network models, defines observability and measurement strategies, establishes data contracts and quality standards, and delivers health, path, and blast-radius insights. Drives cross-functional roadmaps, build-versus-buy decisions, operational tradeoffs, and technical mentorship across large-scale infrastructure systems.

Develop and maintain Python backend services, primarily with Flask, while designing scalable architecture and integrating legacy systems. Build AWS solutions using Lambda, Cognito, SNS, SQS, and DynamoDB; maintain CI/CD pipelines and infrastructure as code with OpenTofu and Terraform. Collaborate in an Agile/Scrum environment, contribute to technical decisions and engineering standards, review code, and mentor junior developers.

Define technical direction for hyperscale Azure Storage components; architect, develop, test, and support highly scalable, secure, compliant, and highly available cloud services. Lead multiple engineering projects, improve reliability, scalability, performance, consistency, and observability, and apply AIOps for incident detection, root-cause analysis, and operational excellence.