Lead Full Stack Engineer, Salesforce

• BE/MS in Computer Science or related technical discipline; advanced degree preferred
• 8+ years of software engineering experience spanning enterprise backend and modern frontend
• Backend: proven experience with data-intensive, multi-threaded, service-oriented cloud products at scale (Java, Spring, REST); demonstrable DB-layer knowlege (schema design, migrations); cloud app development, deployment, and operations (AWS/Azure/GCP, Kubernetes, Docker)
• Frontend / Design Systems: deep expertise in design systems (architecture, governance, adoption, scaling); building and maintaining component libraries and UI platforms with React/TypeScript; expert CSS architecture (BEM, CSS-in-JS, CSS Modules)
• Strong grasp of web accessibility (WCAG 2.1 AA/AAA), browser rendering, performance optimization, and web vitals
• AI-Assisted SDLC experience — hands-on use of Claude / Claude Code or comparable agentic coding tools to accelerate design, implementation, code review, testing, and documentation; ability to orchestrate AI agents and build reusable, trusted automation rather than one-off prompting
• Experience with Agile methodologies and release management; ability to work independently with high autonomy and take initiative
• Excellent communication, collaboration, and mentorship skills in a fast-paced, iterative environment

Desirable

• We're looking for a Lead Member of Technical Staff (LMTS) who pairs deep Design System / UI platform expertise with full-stack cloud product engineering, and who works AI-natively — using AI-assisted SDLC tooling (Claude / Claude Code and similar) as a core part of how they design, build, review, and ship
• You'll join our Informatica Cloud team building the leading AI powered integration-Platform-as-a-Service (iPaaS) — delivering Data Integration, Data Quality, Master Data Management, and Data Governance as cloud services
• As an LMTS on an agile team, you will own architecture and delivery across the full stack — from accessible, scalable design-system-driven UI down through microservices, APIs, and cloud infrastructure
• You will set technical patterns others follow, mentor engineers, and operate at high autonomy in a fluid, fast-paced environment
• Beyond traditional engineering, you'll help establish how the team adopts AI across the software development lifecycle — orchestrating AI agents, building trusted automated pipelines, and converting AI leverage into shipped, high-quality products
• Technology You'll Use:
• Frontend / Design Systems
• ReactJS, TypeScript, JavaScript, HTML5, CSS3
• Design Systems, component libraries & UI platforms
• Redux, RxJS / state management; Webpack, Babel, npm, yarn
• Jest, React Testing Library; visual regression & e2e testing
• Backend / Cloud
• Java SDK, J2EE / Spring Framework, REST, JSON, GraphQL
• Microservices on AWS / Azure / GCP; Kubernetes, Docker
• MySQL, Flyway, schema design & migrations; Chef
• Gradle, Maven; Git, CI/CD pipelines
• AI-Assisted SDLC
• Claude / Claude Code (agentic coding), AI code review, and AI-driven testing/documentation workflows
• MCP-based tooling, prompt/workflow orchestration, and multi-agent automation
• Architect and build across the full stack — from accessible, high-performance UI components and design systems to scalable microservices, APIs, and data-layer designs
• Take architectural ownership of both UI platform / design system initiatives and backend functional areas; own performance and scalability
• Lead frontend architecture and design-system adoption across product teams; collaborate with UX to translate designs into high-quality, WCAG-compliant code
• Drive AI-native engineering practices — orchestrate AI agents to decompose and accelerate work, build trusted autonomous pipelines (code gen, review, test, docs), and set AI-SDLC patterns the broader team adopts
• Lead feature delivery end-to-end with predictable, high-quality releases; provide detailed estimates and meet schedules
• Ensure quality — partner with QA on customer-centric testing, review test specs, minimize regressions across unit / integration / visual / e2e layers
• Mentor engineers on architecture, design, testing, accessibility, and effective use of AI tooling; lead code reviews with constructive feedback
• Communicate and collaborate — give sprint demos to PMs and stakeholders, drive scoping and technical decisions, and produce clear technical documentation
• Support customers and field engineers with troubleshooting complex issues