Top Hybrid Software Engineer Jobs in Los Angeles, CA

Lead a compliance and risk engineering pillar to design, deliver, and operate regulatory automation, AI/ML, and risk-control platforms. Own roadmap, reliability, incident and defect management, stakeholder communication with Legal/Cyber/Compliance, and hiring and growth of software and quality engineering teams across global jurisdictions.

Design, build, and scale cloud-based backend platform components and connectors for ERPs, banks, payments, tax and subledger systems. Lead architecture, deliver highly available multi-tenant SaaS services (API gateway, event bus, identity, scheduler, search, workflow orchestration), ensure performance, security, extensibility and testability, mentor engineers, drive technical decisions, and support deployments and occasional off-hours support.

Lead and grow a software engineering team owning delivery, quality, and operational health. Provide technical oversight for architecture and code quality, drive planning and execution cadence, adopt AI-assisted development tooling, recruit and onboard engineers, remove blockers and manage cross-team dependencies, and partner with product and design to deliver high-impact work.

Design, build, and operate REST and GraphQL APIs, MCP servers, Apache Airflow workflows, and data transformation pipelines using Snowflake and dbt. Collaborate with an experienced applications engineering team supporting front-end interfaces and batch processes. Apply systems engineering and product lifecycle principles while contributing to reliable, scalable software solutions.

Own the end-to-end architecture, development, delivery, and support of a mobile-first event and stakeholder communication platform. Build scalable multi-venue capabilities, enhanced access controls, low-latency offline and mesh networking, and enterprise integrations. Partner with business development on technical discovery, sales demonstrations, privacy and architecture discussions, and pilot deployments. Select cost-effective tooling, collaborate through peer programming, leverage AI development tools, and establish reliable architectural patterns for rapid product growth.

Build and maintain a modern advertiser management platform, including scalable backend services, APIs, microservices, relational data models, and high-performance middleware. Contribute to architecture, system design, troubleshooting, testing, documentation, code reviews, and performance optimization. Collaborate with product, design, and engineering teams while evaluating emerging technologies and AI-assisted development tools.

Designs, develops, tests, maintains, and troubleshoots scalable software applications and components. Responsibilities include requirements analysis, solution and detailed design, Java and framework-based development, CI/CD automation, telemetry, security implementation, automated testing, defect resolution, performance monitoring, application maintenance, and evaluating change requests.

Configures and maintains Qualtrics and Medallia platforms, including surveys, dashboards, reporting, data feeds, APIs, integrations, and automations. Writes SQL queries, processes sample files, troubleshoots systems, tests and debugs programs, supports reporting and analysis, and maintains platform operations. The role also involves reviewing requirements, executing project plans, communicating technical concepts to clients, participating in client meetings, and managing ongoing technical deliverables.

Build and ship new products from zero to one across backend services, APIs, data pipelines, AI-driven workflows, and React front ends. Partner with customers to prototype solutions, design experiments, analyze results, and guide product direction. Establish technical architecture and reusable standards, then scale successful prototypes into production systems. Collaborate with product, platform, data, and operations teams while using AI tools throughout development.

Own end-to-end features across a TypeScript, Next.js, React, Prisma, PostgreSQL, and AWS stack. Build and operate LLM-powered healthcare experiences, including retrieval, structured extraction, tool use, evaluations, tracing, and observability. Advance AI-assisted development practices while maintaining code quality, testing, reliability, and security for sensitive health data. Collaborate with design, clinical, and partner-facing teams, review code, and mentor engineers.