Computer Scientist (Python)

As a Senior Software Developer with proficiency in Python and Generative AI, you will act as a technical leader responsible for architecting and deploying production-grade AI systems. Your role will bridge the gap between AI research and scalable software engineering, focusing on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic workflows. Core Responsibilities: - System Architecture & Build: Lead the build of scalable backend systems and robust architectures for platforms powered by artificial intelligence, ensuring high availability and security. - GenAI Implementation: Build and deploy production-scale Agentic AI workflows and multi-model RAG pipelines using frameworks like LangChain or LlamaIndex. - Model Optimization: Fine-tune LLMs using techniques like LoRA or QLoRA and perform prompt engineering to improve model accuracy and efficiency. - API Development: Develop high-performance RESTful or GraphQL APIs (typically using FastAPI or Flask) to integrate AI models with enterprise applications. - Data & MLOps: Implement data ingestion and preprocessing mechanisms, while overseeing LLMOps practices such as model versioning, monitoring, and CI/CD for AI services. - Leadership & Mentorship: Provide technical guidance to junior developers, conduct rigorous code reviews, and foster a collaborative environment adhering to standard methodologies. Technical Skills & Qualifications: - Advanced Python: Expert-level proficiency (typically 5-8+ years) in Python, including asynchronous programming (asyncio), OOP, and design patterns. - AI Frameworks: Deep experience with Hugging Face, PyTorch, or TensorFlow, and specialized GenAI libraries like LangGraph or CrewAI. - Vector Databases: Hands-on knowledge of vector search and storage solutions like Pinecone, Weaviate, or FAISS. - Cloud Platforms: Strong experience deploying to cloud environments like AWS, Azure, or GCP. - Data Engineering: Mastery of data processing libraries such as Pandas and NumPy, and experience with SQL/NoSQL databases. - DevOps: Proficiency in Docker, Kubernetes, and CI/CD tools (e.g., Jenkins, GitHub Actions) to maintain production stability. Preferred Experience: - Industry Experience: 7+ years in software development, with at least 1-2 years specifically focused on Generative AI or LLM integration. - Education: A Bachelor's degree or higher-level degree or equivalent experience in Computer Science, Engineering, or a related STEM field. About Adobe: Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity, and personalized customer experiences. Adobe's industry-leading offerings enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Adobe is proud to be an Equal Employment Opportunity employer, fostering a company culture where all employees are empowered to make an impact. Join Adobe in driving the next decade of growth and innovation. As a Senior Software Developer with proficiency in Python and Generative AI, you will act as a technical leader responsible for architecting and deploying production-grade AI systems. Your role will bridge the gap between AI research and scalable software engineering, focusing on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic workflows. Core Responsibilities: - System Architecture & Build: Lead the build of scalable backend systems and robust architectures for platforms powered by artificial intelligence, ensuring high availability and security. - GenAI Implementation: Build and deploy production-scale Agentic AI workflows and multi-model RAG pipelines using frameworks like LangChain or LlamaIndex. - Model Optimization: Fine-tune LLMs using techniques like LoRA or QLoRA and perform prompt engineering to improve model accuracy and efficiency. - API Development: Develop high-performance RESTful or GraphQL APIs (typically using FastAPI or Flask) to integrate AI models with enterprise applications. - Data & MLOps: Implement data ingestion and preprocessing mechanisms, while overseeing LLMOps practices such as model versioning, monitoring, and CI/CD for AI services. - Leadership & Mentorship: Provide technical guidance to junior developers, conduct rigorous code reviews, and foster a collaborative environment adhering to standard methodologies. Technical Skills & Qualifications: - Advanced Python: Expert-level proficiency (typically 5-8+ years) in Python, including asynchronous programming (asyncio), OOP, and design patterns. - AI Frameworks: Deep experience with Hugging Face, PyTorch, or TensorFlow, and specialized GenAI libraries like LangGraph or CrewAI. - Vector Databases: Hands-on knowledge of vector search and storage solutions like Pinecone, Weaviate, or FAISS. - Cloud Platforms: Strong experience deploying to cloud environme