Software Engineer, AI Native

Meta is seeking talented engineers to join their teams in building cutting-edge products that connect billions of people around the world. As an AI Native Software Engineer, you will work on complex technical problems, build new AI-powered features, and improve existing products across all platforms. Responsibilities: Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative AI-native application experiences; Build and integrate LLM / generative AI capabilities into product surfaces (mobile, web), including prompt engineering, structured prompting, and context management; Develop and maintain reusable software components for interfacing with back-end platforms, model serving/inference layers, and AI toolchains; Implement retrieval-augmented generation (RAG) patterns (e.g., embeddings + retrieval) and contribute to context-aware and personalized user experiences; Contribute to agentic workflows and AI agents (including human-in-the-loop / expert-in-the-loop designs) to automate tasks and scale impact; Analyze, debug, and optimize code and systems for quality, efficiency, performance, reliability, and cost; Establish effective quality practices for AI features, including evaluation/QA for AI outputs, monitoring, and iterative improvement via feedback loops; Architect efficient and scalable systems that power complex applications and AI-enabled features, identify and resolve performance and scalability issues; Drive end-to-end execution of medium-to-large features with increasing independence, contribute to technical direction within the team; Establish ownership of components, features, or systems with comprehensive end-to-end understanding Qualifications: 6+ years of programming experience in a relevant language OR a PhD + 3 years programming experience in a relevant language; Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience; Experience effectively utilizing AI technologies and tools (e.g., large language models, agents, etc.) to enhance workflows; Experience collaborating cross-functionally and contributing to technical decisions through influence, communication, and execution; Experience building maintainable and testable codebases, including API design and unit testing techniques Required Skills: Programming in relevant languages, AI technologies, Tools, Large language models (LLMs), Generative AI, Prompt engineering, Context management, API design, Unit testing, C/C++, Java, Python, JavaScript, Shell scripting, AI/ML techniques, Fine-tuning, Transfer learning, Few-shot learning, Zero-shot learning, Model distillation, Retrieval-augmented generation (RAG), Embeddings, Transformer-based systems, Machine learning, Recommendation systems, Pattern recognition, Data mining, AI agent design, Human-in-the-loop systems, Software architecture for large-scale applications