Top Software Engineer Jobs in San Diego, CA

Develop and maintain scalable Salesforce solutions using Apex, triggers, asynchronous operations, SOQL/SOSL, and Lightning Web Components. Build REST and SOAP integrations, translate business requirements into secure architectures, troubleshoot Salesforce applications, and collaborate with admins, architects, and stakeholders. Apply version control, deployment, testing, and Salesforce best practices while staying current with platform releases.

Develop and maintain internal applications and AI agents using Microsoft Power Platform, APIs, databases, Copilot Studio, and Azure. Support Agile delivery, automated testing, enterprise integrations, conversational AI, intelligent automation, security and compliance standards, performance monitoring, documentation, and cross-functional solution design. The role is remote with occasional travel and offers foundational development experience.

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.

Leads enterprise software development, platform integrations, custom scripts, and cloud architecture. Manages the software development lifecycle from requirements through deployment, collaborates with stakeholders, mentors engineers, and directly contributes to frontend, backend, and cloud solutions. Oversees third-party enterprise tools, databases, APIs, serverless systems, QA coordination, technical processes, and cross-departmental engineering initiatives.

Builds simulation infrastructure and software-in-the-loop sensor simulation products that help customers test and validate autonomous driving, drone delivery, eVTOL, robotics, and other physical AI systems safely at scale.

Lead and mentor a software engineering team, provide technical guidance, drive architecture and engineering excellence, manage sprint execution, collaborate on product roadmaps, ensure scalable and reliable systems, foster continuous improvement, and support recruiting and onboarding. The role requires balancing technical strategy with business impact while developing high-performing engineers.

Develop and deliver high-volume enterprise applications across the full software development lifecycle. Design, code, test, debug, optimize SQL solutions, troubleshoot complex issues, contribute to scalable architecture, collaborate with technical and business stakeholders, and mentor other developers. Work independently while participating in Agile development and production implementation.

Own and evolve enterprise AWS infrastructure, governance, security, identity, networking, and shared platforms. Build and operate full-stack services in TypeScript and Python, automate infrastructure and delivery, improve monitoring and reliability, manage incidents and on-call operations, and establish audit-ready controls. Partner across engineering and IT, improve production readiness, and mentor engineers while delivering secure, scalable, low-blast-radius systems.

Designs, implements, tests, and supports clinical system integrations between hospital clients and the PerfectServe platform. Responsibilities include coding HL7 interfaces, building SSIS flat-file integrations, coordinating API integrations, validating data feeds, troubleshooting production issues, maintaining documentation, and supporting VPN, sFTP, upgrades, failover, and on-call operations. The role partners with customer technical and clinical teams and internal R&D throughout integration delivery.

Own ambiguous, cross-team product engineering problems from framing through launch and iteration. Partner with product, design, and data; lead architecture, reliability, performance, and technical decisions across the stack. Influence teams without formal authority, mentor engineers, improve engineering practices, use metrics and experimentation, and apply AI throughout software development. Participate in on-call support.