Top Senior Software Engineer Jobs

Build and scale reliable full-stack products for paving contractors, including AI-powered estimating, crew optimization, and automated business insights. Own system performance, security, observability, automation, testing, deployment, and technical standards. Collaborate with engineering, product, design, and company founders while helping shape team culture and development practices.

Design and evolve core data models and durable APIs for complex communications networks. Build, test, operate, and maintain production-grade interfaces and abstractions for heterogeneous physical and logical networks while ensuring compatibility, consistency, quality, and performance. Manage project priorities, timelines, and deliverables within the Spacetime engineering team.

Leads a development team building a classification marking tool for an ICAM Zero Trust program. Responsibilities include providing technical guidance, enforcing code quality, managing project progress, demonstrating solutions, communicating risks, supporting user acceptance testing, maintaining configuration management, preparing deployment packages and documentation, and coordinating customer and software delivery activities.

Develop and maintain end-to-end full-stack software solutions in an agile environment. Design, modify, test, deploy, debug, and monitor applications across UNIX and Linux systems. Build interfaces with third-party products, enhance existing code, resolve complex workflow problems, and collaborate cross-functionally on architecture and system improvements. The role also involves supporting APIs, DevOps practices, automated testing, and software solutions for potentially classified environments.

Develop, integrate, deploy, and maintain robust software applications for federal programs. Responsibilities include providing status estimates, supporting DevSecOps and agile development, working with cloud, containerized, front-end, and back-end systems, automating testing and CI/CD, and troubleshooting Linux-based environments. The role requires an active Secret clearance and expertise in Python, Go, Bash, JavaScript, Kubernetes, virtualization, and command and control systems.

Design, develop, test, and maintain C++ and C# desktop applications using WPF for semiconductor equipment. Architect multithreaded software, integrate applications with hardware and automation systems, optimize performance and reliability, troubleshoot complex integration issues, participate in code reviews, document designs and tests, and contribute to software architecture and technology roadmaps.

Develop and maintain APIs and software applications across the full SDLC. Responsibilities include software architecture, clean and automated coding, code reviews, debugging, testing, deployment, documentation, system monitoring, and collaboration with internal teams and vendors. The role requires extensive Python, AWS, Docker, microservices, and DevOps experience, with independent ownership of development activities in a remote environment.

Design, build, and operate secure, scalable Java microservices for a high-traffic consumer platform. Develop production LLM features using RAG, agentic workflows, and tool-use patterns. Lead design discussions and code reviews, improve quality and testing, partner with product, security, and platform teams, and resolve performance and scalability issues. Deploy and operate services on AWS using Docker and Kubernetes while applying event-driven architecture, CI/CD, infrastructure as code, and automated testing.

Build and optimize distributed compute infrastructure for large-scale analytical and AI workloads. Responsibilities include improving query execution, scheduling, resource allocation, reliability, workload routing, and compute efficiency across Spark and related systems. The role involves debugging performance bottlenecks, optimizing joins, scans, shuffles, caching, partitioning, and memory usage, and working with lakehouse formats and cloud object storage. Candidates will implement workload optimization algorithms and may contribute to open source or research.

Build foundational lakehouse infrastructure for exabyte-scale AI data environments. Responsibilities include metadata and transaction systems, table maintenance, schema and partition evolution, snapshot isolation, compaction, clustering, file-layout optimization, object-store performance, columnar-format optimization, and query performance across major lakehouse engines. The role also involves debugging distributed systems, implementing compression and data-efficiency algorithms, and contributing to open-source or research efforts.

Build and own large-scale backend and full-stack systems supporting AI agents, data integrations, sync engines, and construction financial products. Design major subsystems, make architecture and build-versus-buy decisions, debug complex production issues, improve scalability and performance, and mentor engineers. Work across cloud infrastructure, distributed systems, legacy on-premise integrations, caching, data consistency, and AI-powered workflows while collaborating directly with founders and customers.

Own and lead the technical direction of a major codebase section while designing, building, testing, documenting, and maintaining secure, scalable API-based decisioning products. Partner with product, engineering, and security teams on agile delivery, troubleshoot production issues, meet SLA requirements, and participate in an on-call rotation.

Design, develop, and deploy resilient, low-latency microservices and event-driven solutions for Zscaler’s cloud security control plane. Own services from API tiers through backend systems, modernize platforms using API-first architecture, maintain coding quality through reviews and TDD/BDD, and collaborate with Product, DevOps, and architecture teams. Use Docker, Kubernetes, cloud platforms, distributed data patterns, databases, and AI-powered engineering tools to build scalable systems.

Design and scale highly available backend services for an AI-powered manufacturing platform. Build AWS-based event-driven systems with Node.js, REST/GraphQL APIs, and database integrations. Use AI coding agents while validating correctness, write tests and documentation, improve observability and reliability, debug production issues, and collaborate with product, frontend, and infrastructure teams. Contribute to technical design, code reviews, engineering best practices, and responsible adoption of AI-assisted development.

Own technical strategy and architecture for agent infrastructure, tax computation, data pipelines, evaluation systems, and filing workflows. Design and ship highly available, correctness-critical systems; lead infrastructure investments; make build-versus-buy decisions; create technical roadmaps; advise founders and engineering leadership; and raise engineering quality through designs, code, reviews, and technical direction without direct authority.

Own a major product surface, write and review production code, make long-term architecture and build-versus-buy decisions, and maintain high correctness standards. Collaborate directly with founders on roadmap, improve evaluation systems, and optionally lead a small engineering pod through code reviews, one-on-ones, and technical mentorship. Work involves ambiguous problem definition, end-to-end system ownership, and potentially LLM-powered platforms, cloud infrastructure, compliance-aware design, and internal engineering tools.

Build and operate distributed systems powering Lambda’s GPU cloud, including APIs, control planes, schedulers, workflows, and operational tooling. Own systems through architecture, implementation, deployment, observability, on-call, incident response, and continuous improvement. Improve reliability, performance, security, and scalability while collaborating across infrastructure, networking, storage, security, and SRE teams. Senior engineers lead complex domain work; Staff engineers shape cross-team architecture and mentor others.

Design and build Lambda’s managed Kubernetes platform for large-scale AI workloads. Responsibilities include developing control-plane services, operators, controllers, cluster lifecycle automation, GPU-aware scheduling, inference infrastructure, autoscaling, internal deployment tools, observability, and production support. The role requires deep Kubernetes and distributed systems expertise, strong Go and Python skills, and collaboration across networking, storage, compute, and AI infrastructure teams.

Own Android accessibility across Slack, including Compose component fixes, TalkBack troubleshooting, automated accessibility testing infrastructure, VPAT compliance, regression testing, and cross-platform planning. Provide accessibility guidance to feature teams, mentor engineers, coordinate with QA vendors, and promote best practices through documentation, onboarding, and presentations.

Lead the design, development, testing, and optimization of large-scale data pipelines and cloud-native data platforms. Build Python and PySpark applications, manage ETL workflows, Snowflake environments, data lakes, and AWS services, and promote secure engineering, CI/CD, automated testing, and responsible AI-assisted development. Mentor engineers, participate in code reviews, and lead technical delivery initiatives.

Design and build Lambda’s managed Kubernetes platform for large-scale AI workloads. Responsibilities include developing control-plane services, operators, controllers, cluster lifecycle automation, GPU-aware scheduling, inference platform services, internal deployment tools, observability, and resilient distributed systems. The role involves collaboration across networking, storage, compute, and security teams, production troubleshooting, and participation in an on-call rotation.

Build and operate distributed systems powering Lambda’s GPU cloud, including APIs, control planes, schedulers, workflows, and operational tooling. Own systems through design, implementation, deployment, observability, on-call, incident response, and continuous improvement. Improve reliability, performance, security, scalability, and operability while collaborating across infrastructure, networking, storage, security, SRE, and product teams. Senior engineers lead complex team-level work; Staff engineers additionally shape cross-team architecture and mentorship.

Develop scalable web platform services, programming operations tools, content workflow experiences, and developer-facing capabilities. Responsibilities include software design, coding, testing, debugging, documentation, performance optimization, cloud technology evaluation, accessibility, SEO, code reviews, and Agile delivery. The role supports reliable web application infrastructure and requires completing project deliverables with limited supervision.

Designs and directs development of scalable software systems using AI-assisted engineering practices. Owns architecture, APIs, data models, testing strategy, security, reliability, observability, deployment, and production operations. Decomposes work for AI agents, validates generated code and tests, leads incident response, and coaches engineers on effective AI-enabled development. Requires full-stack experience, modern server-side development, event-driven systems, cloud infrastructure, regulated-data security, and production use of agentic AI.

Develop and enhance Cadence’s Xcelium RTL/logic simulator and timing-constraint verification technology. Design and optimize graph algorithms for massive SDC constraint graphs, perform C/C++ performance tuning, reduce compilation time and memory usage, write specifications and unit tests, and collaborate with globally distributed engineering teams.