Top Hybrid Software Engineer Jobs

Customize and configure ServiceNow applications and workflows, gather and document user and technical requirements, analyze system interactions, support Service transformation teams, maintain environments and release upgrades, troubleshoot complex issues, and train users and team members. Ensure consistency across development, test, and production environments and continuous process improvement.

Build and maintain the full-stack platform connecting Blissway hardware to drivers, partners, and agencies. Own public user surfaces, partner integrations (DMVs, mailhouses, fleet vendors, ACH), platform/deployment tooling, service infrastructure, and internal access management. Ensure secure, robust, production-ready systems and tooling that support a fast-moving, small engineering team.

Own Perk’s global go-to-market engineering strategy, architecture, tooling, and roadmap. Build production-grade Clay automations, Salesforce integrations, orchestration systems, and AI-agent workflows using code and modern data infrastructure. Automate prospecting, seller workflows, account intelligence, and revenue operations while measuring commercial impact. Lead and develop a senior international team, partner with sales and revenue leaders, and establish engineering standards for scalable, monitored, tested, and recoverable systems.

Lead the design, development, deployment, and long-term operation of complex full-stack systems and features. Decompose ambiguous customer problems, manage data models and production systems, monitor SLAs, diagnose incidents, and make architectural decisions. Collaborate with Product, Design, Data Analytics, and Lifecycle Comms while mentoring engineers and improving engineering processes, tooling, and on-call practices. Work primarily with TypeScript, GraphQL, Temporal, Postgres, and AWS, using AI tools responsibly.

Lead the engineering team to develop Tulip's new agent-native app-building product, managing technical architecture and fostering AI-driven development practices.

Own the architecture and technical direction of a cloud-native core simulation platform supporting reinforcement learning, controls validation, and CI/CD testing. Design distributed systems and high-throughput pipelines capable of generating millions of experience hours daily. Define platform abstractions, APIs, performance and reliability standards, and the product roadmap. Partner with Controls, AI Research, and Perception teams, resolve systemic bottlenecks, review designs, and mentor senior engineers.

Lead the technical strategy, architecture, quality, reliability, security, and scalability of Rain’s approximately 50-person engineering organization. Oversee critical payment, wallet, ledger, settlement, and partner-integration systems; establish engineering standards, SLOs, incident practices, and developer tooling; review high-impact designs; and develop engineering managers and technical leads. Partner with Product, Risk, Compliance, leadership, board members, banking partners, and customers while planning for significant transaction-volume growth.

Build and own the decision engine powering hospital staffing recommendations, alerts, and workflows. Design systems that balance staffing rules, hospital policies, patient needs, and operational constraints. Partner with product, design, engineers, and clinical leaders to create explainable, trustworthy automation. Improve the product through customer feedback, production data, and real-world outcomes while determining where automation should end and human judgment should remain.

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.

Design and build scalable, reliable, observable, and well-tested backend and distributed systems. Work in AI-assisted development workflows by decomposing problems, validating AI-generated outputs, and using tools such as Claude and code assistants. Contribute to architecture, data modeling, APIs, service boundaries, documentation, and technical direction while mentoring peers and collaborating across Product, UX, and Engineering.