Meta is seeking experienced engineers to join AI Solutions and Automation + Support (ASA+S), where we apply state-of-the-art AI and autonomous agents to the products and support experiences used by billions of people. We build agents that resolve real problems for users, creators, and businesses, along with the platforms, evaluation systems, and model infrastructure that let those agents ship safely and at scale. This is applied AI where research meets production: you'll build and optimize LLM and agentic systems, design the data and evaluation foundations that make them trustworthy, and take frontier techniques from prototype to production. It's deliberately high-leverage work; what we prove once becomes a platform that other teams build on. If you want to work on genuinely novel agent problems and see your work reach real users quickly, this is the right team for you.

Qualifications:

12+ years of programming experience in a relevant language OR 8+ years experience with a PhD Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Experience influencing and advising executive stakeholders across organizations Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Experience communicating and working across functions to drive solutions Proven track record of planning multi-year roadmaps in which short-term projects ladder to the long-term mission Experience driving large cross-functional/industry-wide engineering efforts Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Master's degree or PhD in Computer Science or a related technical field Understanding of information retrieval concepts, such as indexing, querying, and ranking Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience building large-scale, multi-stage reasoning systems in high-QPS production environments, including LLM post-training (e.g., reinforcement learning, fine-tuning) to improve quality and cost Track record of designing and implementing agentive AI systems and frameworks (e.g., agent harnesses, multi-agent orchestration) in production