Lead Full Stack Engineer

Salesforce•Redwood City, CA

1d•$172,500 - $285,800•Onsite

About The Position

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.

Requirements

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.

Nice To Haves

Contributions to open-source UI libraries or design systems.
iPaaS / data integration, data quality, MDM, or data governance domain experience.
Building AI/agentic developer tooling, MCP servers, or LLM-integrated internal platforms.
CI/CD automation for both frontend and backend applications.

Responsibilities

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.