Computer Scientist 2 at Adobe
Who can apply
The employer hasn’t stated batch, branch or CGPA requirements for this role. Upload your résumé to see how well you match.
About this role
The Opportunity The Lead Growth & AI Platform Engineer will play a pivotal role in transforming Adobe.com's Growth and Martech Engineering (GME) platform into an AI-first engineering ecosystem. This role sits at the intersection of Full Stack engineering, AI, Martech technology and platform architecture building the next generation of internal engineering platforms that power campaign creation, validation and experimentation at scale. As Adobe shifts toward agentic Customer Experience Orchestration (CXO), this engineer will help design and build the core AI-powered platforms that automate engineering workflows, campaign creation, validation and Martech operations. What you'll do Develop and build advanced AI-native platforms for Growth Engineering that enable campaign orchestration, experimentation and Martech automation. Architect reusable engineering services and platform capabilities that can be demonstrated across Adobe.com's Growth, Martech and Personalization organizations. Build agentic engineering workflows that automate campaign development, validation, content generation and operational engineering tasks. Design scalable platform APIs, orchestration services and integration layers spanning Adobe Experience Cloud, internal Adobe platforms and AI services. Lead technical design and implementation of production-grade AI capabilities, including LLM integration, retrieval systems, MCP connectors, agent frameworks and autonomous workflows. Drive platform architecture decisions around scalability, observability, reliability, security and maintainability. Partner closely with architects, product managers and engineering leaders to define the long-term technical roadmap supporting Growth Engineering. What you need to succeed Develop production AI systems beyond simple LLM integrations, including orchestration, agent systems, tool calling, structured outputs, retrieval pipelines, evaluation structures and self-directed processes. Experience building engineering prod
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