Top Software Engineer Jobs

Entry-level hybrid role supporting clinical laboratory operations through workflow analysis, software and solution development, algorithm creation, clinical genetic data management, and project coordination. Responsibilities span software engineering, bioinformatics, analytics, process management, diagnostic reporting, and high-throughput workflow optimization. The role requires learning genetics, biology, healthcare standards, and laboratory procedures while collaborating across technical, scientific, operational, and business teams.

Build and deploy AI-powered marketing solutions for enterprise customers. Responsibilities include scoping technical requirements, developing proof-of-concepts, integrating customer marketing infrastructure, building data pipelines and custom functionality, deploying AI workflows, supporting customer success, and translating deployment insights into reusable product capabilities. The role requires close collaboration with sales, deployment strategists, engineering, product, and growth teams in an in-person San Francisco environment.

Assists with designing, developing, testing, debugging, documenting, and integrating software for aerospace applications. Collaborates with cross-functional teams, participates in code reviews, supports software quality and performance, and helps integrate software with hardware systems. The role requires a relevant bachelor’s degree, programming proficiency, and the ability to obtain and maintain a Secret U.S. security clearance. It is hybrid with occasional travel.

Seeking a web developer to build and maintain websites or web applications. The posting provides no additional details about responsibilities, qualifications, technologies, compensation, or work arrangements.

Build and improve operator and customer software using TypeScript, React, and Rust. Develop Electron application features, collaborate with product and vehicle engineers, and own features from requirements through testing, documentation, and post-release support. Contribute to full-stack product development involving data models, APIs, performance, and reliability. This junior role emphasizes learning quickly, communication, independent problem-solving, and practical software development 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.

Build scalable Python backend services and distributed geospatial data pipelines for sonar and bathymetric datasets. Architect AWS cloud infrastructure, APIs, storage, and edge-processing systems for AUVs. Integrate AI/ML models for target detection and data classification, optimize cloud-native geospatial formats, and contribute to containerization, infrastructure-as-code, and CI/CD. The role bridges real-time onboard processing with post-mission cloud analysis.

Lead full-stack design, development, and deployment of scalable applications using FastAPI and Vue.js. Integrate AI dev tools to improve workflows, manage AWS cloud infrastructure, build high-performance APIs, champion best practices, troubleshoot performance issues, and mentor junior engineers while collaborating cross-functionally.

Build and own user-facing features and core platform architecture across frontend, backend, and ML pipelines. Integrate AI workflows (LLMs, embeddings) for curriculum generation and automated evaluation. Manage end-to-end development: requirements, design, implementation, CI/CD, testing, observability, and iteration while collaborating with product, design, ML, and customer teams.