Summary
Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
The people here at Apple don't just build products they build the kind of wonder that's revolutionised entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
Description
As a Software Engineer, you are an integral part of a small data-centric team driving large-scale data infrastructure and processes development, implementation, and improvement. Our organization thrives on collaborative partnerships. Join and play a key role in developing and driving the adoption of Data Mesh and data-centric micro-services. Apple's Manufacturing Systems and Infrastructure (MSI) team is responsible for capturing, consolidating and tracking all manufacturing data for Apple's products and modules worldwide.
Our tools enable teams to confidently use data to shape the next generation of product manufacturing at Apple. We seek a practitioner with experience building large-scale data platforms, analytic tools, and solutions. If you are passionate about making data easily accessible, trusted, and available across the entire business at scale, we'd love to hear from you.
Responsibilities
- As a GenAI Backend Engineer, you will partner with cross-functional teams including product, data science, and platform engineering to translate business requirements into scalable, reliable, and high-performance backend systems. The ideal candidate brings deep expertise in cloud-native architectures, AI/ML integration, and modern software engineering best practices, with a consistent track record of delivering complex, production-grade systems at scale.
- In this role, you will:
- Design, develop, and maintain scalable GenAI backend services and APIs that power intelligent product features
- Build and optimize LLM-powered pipelines including RAG, agents, tool-use, and multi-turn conversation flows
- Partner with machine learning, product, and DevOps teams to move AI experiments from prototype to production with high reliability and low latency
- Implement monitoring, alerting, and evaluation frameworks to ensure the quality, safety, and performance of GenAI outputs in production
- Lead POCs and technical spikes to evaluate emerging GenAI tools and influence the team's technology direction
- A self starter, forward-thinking person to consider implications of choices and communicate key decision junctures driving technical design decision-making
- Write clean, well-tested, and documented code with a strong focus on maintainability and scalability
Minimum Qualifications
- 7-12 years of strong proficiency in Python with hands-on experience building production-grade backend services using FastAPI or Flask, including async/await patterns and Pydantic data validation
- Hands-on experience integrating and working with LLM APIs (OpenAI, Anthropic Claude, Gemini, or similar), including prompt engineering, function/tool calling, and response handling
- Experience building and deploying RAG (Retrieval-Augmented Generation) pipelines with vector databases such as Milvus, Pinecone, Weaviate, pgvector, or FAISS
- Strong command of PostgreSQL / MySQL, query optimization, indexing strategies, and ORM frameworks like SQLAlchemy
- Experience with distributed systems and microservices architecture, including service discovery, inter-service communication (REST, gRPC), and fault tolerance patterns
- Proficiency with message queues and event-driven architecture using tools like Redis, RabbitMQ, or AWS SQS
- Experience deploying and managing services on Kubernetes and AWS (EKS, Lambda, S3, SQS, RDS), including Docker containerization and CI/CD pipelines
Preferred Qualifications
- B.Tech. / B.E. in Computer Science or equivalent field with hands-on software engineering experience, including 2+ years working directly with LLMs or Generative AI systems in a production
- environment.
- Experience with LangChain, LlamaIndex, or similar orchestration frameworks for building multi-step LLM pipelines and agentic workflows
- Working knowledge of streaming inference, token optimization, and prompt caching strategies to reduce latency and cost
- Exposure to observability and evaluation frameworks for LLM outputs (hallucination detection, faithfulness scoring, latency monitoring) using tools like CloudWatch, Splunk, or Datadog
At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple's workplace
Role Number: 200663838-0321
