Senior GenAI Engineer, Apple Cloud AI - Jobs - Careers at Apple
- Design and development of platform capabilities such as agent orchestration, agentic RAG, LLM model configuration, prompt optimization tooling, and fine-tuning and RL pipelines that meet the highest standard in security and safety
- Drive efforts around LLM and Agent optimization, including caching, prompt tuning, and latency improvements, ensuring efficient and cost-effective model usage across agentic systems
- Define and drive the technical roadmap, and strategy for Apple Cloud AI GenAI components, enabling scalable and secure development and deployment of agentic systems and harnesses
- Collaborate with engineering, product, and operations teams across Apple to ensure effective adoption of GenAI capabilities in high-impact workflows
- Partner with stakeholders to build reusable AI agents that enhance productivity, automate reasoning tasks, and integrate securely with internal systems and tools
- Mentor new hires and fellow engineers, fostering growth in technical depth and platform mindset
- Establish best practices and processes that ensure engineering excellence, operational sustainability, and a seamless developer experience
- Promote a healthy, inclusive, and innovation-driven team culture with a focus on experimentation, learning, and long-term platform impact
- 4+ years of machine learning and software development experience
- 1+ years of experience as a technical lead, guiding teams through complex design decisions and setting high benchmarks for code quality, performance, and scalability
- Hands-on experience designing and building GenAI platforms that allow users to create, configure, and deploy AI Agents supporting features like agent orchestration, prompt engineering, RAG integration, and model selection
- Experience building AI agents capable of complex multi-step reasoning and tool usage, with a focus on reliability, traceability, and composability
- Experience building and deploying Agent Harnesses, including integrations with Agent Memory and Context, MCP and tools, and runtime secure environments (Agent Sandboxes)
- In-depth understanding of security primitives for AI Agents and Harnesses including policy enforcement, MCP/tools access control, runtime security, drift and hallucination detection for long horizon agents.
- In-depth understanding of large language models (LLMs) and their application in AI-driven solutions, including inferencing, embedding, and knowledge base integration (RAG) for improved data retrieval and contextualization
- Knowledge of LLM inference optimization techniques, including prompt tuning, caching, quantization, and latency reduction across different model families
- Strong programming skills in Python, Java, or similar languages, with an emphasis on AI/ML systems development and platform engineering
- Demonstrated ability to work cross-functionally and influence product development through a combination of technical leadership and user-centered thinking
- Passion for operational excellence, automation, and delivering scalable, developer-friendly AI infrastructure
- B.S, M.S. or PhD Degree in Computer Science/Engineering, or equivalent work experience
- Expertise in 3rd party Cloud Environments (Google Cloud and AWS)
- Hands on experience in using Kubernetes as orchestration layer
- Proven experience in customizing foundation models to improve task-specific performance and domain alignment
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Required Skills
Required Languages
🇬🇧 English