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Tier-1 brand, mid-level SDE, popular GenAI skills and metro location drive high applicant competition.
ML/LLM and production distributed systems skills are transferable but require specialized AI experience.
Explicit 3–5 years plus mandatory LLM, backend, and distributed systems skills makes filters strict.
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Develop and maintain AI-powered applications, backend services, and distributed systems focused on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
Build APIs, microservices, and agentic workflows to integrate AI capabilities into Adobe products and platforms.
Ensure scalability, reliability, and performance of enterprise-scale AI systems and contribute to improving engineering efficiency and product capabilities.
3-5 years of experience building software applications, backend services, or distributed systems.
Strong programming skills in Python, Java, or similar modern languages.
Hands-on experience with Large Language Models (LLMs), AI frameworks, and familiarity with RAG architectures, vector databases, and embeddings.
Experience with databases (SQL/NoSQL), distributed systems concepts, APIs, microservices, cloud native application development, and cloud platforms like Azure, AWS, or GCP.
Experienced in building scalable AI systems using LLMs and RAG with a strong foundation in distributed systems and backend services.
Practiced in implementing agentic workflows, multi-agent systems, AI orchestration, and knowledge systems at enterprise scale.
Comfortable working within fast-paced engineering teams developing AI-powered products, with exposure to Kubernetes, MLOps, or LLMOps as a plus.