Top Hybrid Software Engineer Jobs

Leads the AV Data Processing and Services team, combining hands-on software engineering with people management. Owns architecture and roadmap for petabyte-scale distributed data pipelines, storage, batch inference, streaming, simulation, cloud infrastructure, observability, reliability, and cost optimization. Recruits and mentors engineers, establishes SLAs, manages incidents, and translates cross-functional requirements into dependable technical deliverables.

Develop and operate scalable, highly available SaaS data-platform microservices. Responsibilities include designing systems, implementing features, optimizing performance, troubleshooting, collaborating with product, UX, and TechOps teams, participating in Agile delivery, and serving on-call rotations. The role involves distributed systems, data processing, storage, event-driven architecture, containerization, and full-stack development.

Build a greenfield, low-latency algorithmic execution platform in C++. Responsibilities include developing FIX gateways, exchange market data feed handlers, venue connectivity, pre-trade risk controls, platform infrastructure, audit logging, and algorithmic strategy migration. The role requires optimizing critical paths for microsecond-level performance while integrating U.S. exchanges and dark venues. Future work includes multi-asset execution, research and backtesting, and international market expansion.

Build and maintain reproducible research infrastructure for evaluating digital-twin and large language model systems. Responsibilities include automating experiments, implementing deterministic measurement pipelines, managing versioned datasets and human-participant data, maintaining research-production alignment, monitoring evaluation validity and compute costs, and supporting documented coding workflows. The role requires strong Python, data pipeline, cloud, concurrency, machine learning, and software engineering skills, with preferred experience in LLM systems, model fine-tuning, inference serving, experiment tracking, and generative agents.

Build and evolve scalable, performant software services supporting production AI systems. Responsibilities include writing quality code, designing cloud-neutral microservices, optimizing and deploying AI models, contributing to architecture and design discussions, leading the software development lifecycle, mentoring engineers, and collaborating cross-functionally. The role requires expertise in Go or another major programming language, Python, DevOps technologies, cloud architecture, databases, and scalable service development.

Develop, configure, and maintain the ServiceNow platform (ITSM, HRSD). Build flows, business rules, client scripts, ATF tests, and integrations (REST/SOAP). Troubleshoot platform issues, document solutions, collaborate with cross-functional teams, and participate in Agile ceremonies.

Lead and scale the Client Connector Portal engineering team, guide architecture and design, oversee cloud operations and service ownership, and partner with product management on the roadmap. The role requires managing enterprise Java development teams, improving scalability and reliability, adopting AI-driven development practices, and delivering secure, high-impact cloud services.

The Software Engineer will develop automated solutions, maintain systems, enhance software performance, and support a government program through collaboration and leadership.

Architect and evolve Navan’s frontend platform across 20+ engineering teams. Build micro-frontend infrastructure, shared libraries, developer tools, AI-assisted coding workflows, testing standards, and reusable AI experience components. Drive framework migrations, performance optimization, reliability, security, and adoption of engineering standards. Collaborate with Security, AI platform, Product, and engineering teams while mentoring developers and measuring delivery, quality, reliability, and AI workflow outcomes.

Leads the design, development, and rollout of integrations and data pipelines for BrazeAI Decisioning Studio. Builds fault-tolerant, event-driven ingestion and activation systems across warehouses, APIs, file drops, and streaming sources. Owns production reliability, observability, incident resolution, multi-region compliance, and data residency. Partners with data science and product teams, mentors engineers, and establishes technical direction and engineering standards.