Full Job Description
Description
What happens when the world's most innovative engineers collaborate with the world's most creative storytellers? TV gets reinvented. Meet the re-inventors: Apple Services' Media Engineering (ASE Media).
ASE Video teams have embarked on a journey to build the next-generation sports and media experience. In the ASE Video teams, we work every day to create products that enrich people's lives. The teams build and manage the Apple TV app as well as tvOS, which redefined and refined the way people watch movies, TV shows, sports, and so much more. The ASE Video group is looking for a Software Engineer to join our Universal Media Engineering team. The Universal Media Engineering team leads the data platform and related tools that power the Apple TV app.
We are looking for enthusiastic, self-starting individuals who can bring new ideas and innovations to the platform and push the boundaries of scalability, latency, and quality. We're looking for a software engineer who is passionate about building highly scalable backend systems, developing internal platforms, and applying modern AI technologies to solve complex engineering problems. Does this sound like you? If so, we want to speak with you.
As a software engineer, you will be responsible for designing and building services that directly impact millions of users. You'll collaborate closely with a diverse set of teams that include engineering, project management, business operations, design, and curation, working towards a common vision of delivering the best possible Apple TV experience for our customers.
Beyond delivering production-quality software, you'll play an important role in accelerating the adoption of AI-powered development practices and intelligent applications. You'll identify opportunities to incorporate generative AI into products, engineering workflows, and operational processes, helping teams deliver software faster, improve reliability, and unlock new capabilities.
Minimum Qualifications
5+ years of professional software engineering experience, with demonstrated ability to own features throughout the software development lifecycle, from design and development through production support.
Experience designing and developing scalable, highly observable, and resilient backend services and RESTful APIs.
Strong proficiency in Java (and one or more backend programming languages such as Kotlin, Go, or Python).
Solid understanding of distributed systems, concurrency, networking, and service-oriented architectures.
Experience with databases, data modeling, and cloud-native application development.
Experience with containerized applications, CI/CD pipelines, and modern software development practices.
Hands-on experience building production applications powered by Large Language Models (LLMs), including integrating models into backend services and working with concepts such as prompting, retrieval, structured outputs, or tool/function calling.
Strong analytical, communication, and collaboration skills.
Ability to solve problems given incomplete or partial data and/or requirements.
Driven to deliver high-quality solutions consistently and quickly.
Bachelor's degree in CS/CE/EE or a related technical field, or equivalent industry experience.
Preferred Qualifications
Experience building large-scale distributed systems, data pipelines, or event-driven architectures.
Familiarity with one or more of these technologies: NoSQL databases (Cassandra, DynamoDB), messaging systems (Kafka/RabbitMQ), Solr/Elasticsearch, Redis, SQL (PostgresSQL, MySQL), Spring Framework/Spring Boot, Docker, Kubernetes etc.
Experience building advanced LLM applications using Retrieval-Augmented Generation (RAG), vector databases, semantic search, AI agents, and production-grade evaluation and guardrails.
Experience integrating foundation models through platforms such as OpenAI, Anthropic, Google Gemini, Azure OpenAI, AWS Bedrock, Hugging Face, or self-hosted open-source models.
Experience evaluating AI systems using model evaluation frameworks, prompt testing, guardrails, observability, and performance benchmarking.
Experience mentoring peers and influencing technical direction through collaboration, technical leadership, and knowledge sharing.
