Sr. Agentic Service Engineer

Role Overview: As a Senior Software Engineer for AI Agents at Apple, you will define the technical vision and own the architectural evolution of the platform infrastructure that enables AI agents to thrive at Apple scale. Your role will involve driving strategic platform decisions, mentoring engineering teams, and influencing technical direction. You will be responsible for building and optimizing the platform supporting the agentic ecosystem, including data pipelines, compute orchestration, monitoring, and reliability systems. Key Responsibilities: - Define modular agent architectures integrating powerful foundation models, including Large Language Models (LLMs) and beyond. - Architect platform solutions that deliver flexibility, resilience, and cost optimization while meeting stringent security and privacy requirements. - Collaborate with AI/ML teams, data scientists, and infrastructure organizations to translate agentic workload requirements into scalable platform capabilities for rapid innovation. - Lead multi-functional technical initiatives, establish platform engineering standards, and drive the strategic roadmap for AI agent infrastructure. - Drive real-time orchestration of agents interacting with data, APIs, and users to unlock smarter, faster, and more adaptive applications at scale. Qualifications Required: - 5+ years of experience in ML engineering with a focus on large-scale software system design and implementation. - Strong understanding of generative AI models, particularly Large Language Models (LLMs), with proven experience in building complex agentic systems using LLMs. - Proficiency in Python programming, with a background in developing scalable and robust services using FastAPI or similar frameworks. - Experience in Machine Learning, specifically with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), and Generative AI. Additional Company Details: The company prefers candidates with a Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields, or equivalent experience. Effective communication skills, both written and verbal, with technical and non-technical multi-functional teams are highly valued. Candidates with a proven track record of building enterprise-grade ML pipelines in cloud environments and extensive knowledge of popular LLMs such as Gemini, Claude, and GPT are desired. Experience with building AI agents, LLMs for tool use, and Multimodal-LLMs is a plus, along with familiarity with reinforcement learning, distillation, RLHF fine-tuning, RAG/VectorDB, LLM uncertainty quantification, and ML frameworks such as PyTorch, TensorFlow, and scikit-learn. Understanding of AI memory systems and experience with platform engineering or developer experience platforms are advantageous, as well as hands-on experience with cloud services and containerization technologies.,