Job
Description
As a Senior Software Development Engineer at Adobe, you will lead crafting, developing, and deploying scalable software solutions that use modern Generative AI (GenAI) models and infrastructure. This position combines classic senior software engineering skills with advanced AI/ML methods, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic systems! Key Responsibilities: - Design & Development: Architect and implement scalable GenAI agents, applications, and microservices using modern protocols and standard processes. - AI Integration: Collaborate with AI scientists and data engineers to integrate machine learning models, such as LLMs and multi-modal AI, into the application architecture. - Infrastructure & Deployment: Develop and manage large-scale API infrastructure along with CI/CD pipelines. Use containerization technologies like Docker and Kubernetes and cloud services such as AWS, GCP, and Azure to support smooth deployment and monitoring. - RAG & Optimization: Implement solutions using RAG (Retrieval-Augmented Generation) patterns, timely engineering, and model fine-tuning techniques to optimize AI performance and cost. - Quality & Mentorship: Enforce code quality, conduct comprehensive code/build reviews, and provide technical leadership and mentorship to junior team members. - Problem Solving: Triage, debug, and resolve complex issues across multiple systems, ensuring the reliability, performance, and security of GenAI solutions. Required Qualifications & Skills: - Experience: 10+ years of professional software development experience, with at least 2-3 years of experience specifically with GenAI techniques or related concepts. - Technical Proficiency: Extensive knowledge in one or more programming languages, chiefly Python, and associated libraries (e.g., LangChain, Transformers, PyTorch/TensorFlow). - Cloud & DevOps: Practical experience working with cloud platforms (AWS, GCP, or Azure), containerization tools (Docker, Kubernetes), and continuous integration and delivery pipelines. - AI Knowledge: Strong understanding of AI/ML infrastructure, model deployment/evaluation, vector databases, and AI-specific concepts like agentic workflows. - Education: A Bachelor's degree or equivalent experience in Computer Science, Software Engineering, or a related technical field. - Soft Skills: Excellent problem-solving, analytical, and communication skills. Ability to work effectively in an agile environment. As a Senior Software Development Engineer at Adobe, you will lead crafting, developing, and deploying scalable software solutions that use modern Generative AI (GenAI) models and infrastructure. This position combines classic senior software engineering skills with advanced AI/ML methods, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic systems! Key Responsibilities: - Design & Development: Architect and implement scalable GenAI agents, applications, and microservices using modern protocols and standard processes. - AI Integration: Collaborate with AI scientists and data engineers to integrate machine learning models, such as LLMs and multi-modal AI, into the application architecture. - Infrastructure & Deployment: Develop and manage large-scale API infrastructure along with CI/CD pipelines. Use containerization technologies like Docker and Kubernetes and cloud services such as AWS, GCP, and Azure to support smooth deployment and monitoring. - RAG & Optimization: Implement solutions using RAG (Retrieval-Augmented Generation) patterns, timely engineering, and model fine-tuning techniques to optimize AI performance and cost. - Quality & Mentorship: Enforce code quality, conduct comprehensive code/build reviews, and provide technical leadership and mentorship to junior team members. - Problem Solving: Triage, debug, and resolve complex issues across multiple systems, ensuring the reliability, performance, and security of GenAI solutions. Required Qualifications & Skills: - Experience: 10+ years of professional software development experience, with at least 2-3 years of experience specifically with GenAI techniques or related concepts. - Technical Proficiency: Extensive knowledge in one or more programming languages, chiefly Python, and associated libraries (e.g., LangChain, Transformers, PyTorch/TensorFlow). - Cloud & DevOps: Practical experience working with cloud platforms (AWS, GCP, or Azure), containerization tools (Docker, Kubernetes), and continuous integration and delivery pipelines. - AI Knowledge: Strong understanding of AI/ML infrastructure, model deployment/evaluation, vector databases, and AI-specific concepts like agentic workflows. - Education: A Bachelor's degree or equivalent experience in Computer Science, Software Engineering, or a related technical field. - Soft Skills: Excellent problem-solving, analytical, and communication skills. Ability to work effectively in an agile environment.
