> Markdown version of [/jobs/ext/2590990-ai-and-infrastructure-engineer](https://www.wearedevelopers.com/jobs/ext/2590990-ai-and-infrastructure-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI and Infrastructure Engineer - **Company:** Apple Inc. - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Sql Data Warehouse, Artificial Intelligence, Airflow, Data Analysis, Architectural Patterns, Cloud Computing, Computer Programming, Databases, Continuous Integration, Command-Query Responsibility Segregation (Software Development), Information Engineering, Data Mart, Web Development, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Prometheus, Service Development Studio, Software Engineering, TypeScript, Pytorch, Large Language Models, Snowflake, Grafana, Prompt Engineering, Kubernetes, Information Technology, Deployment Automation, HuggingFace, Machine Learning Operations, Terraform, Data Pipelines, Databricks, Web Api - **Published:** August 27, 2026 - **Apply:** https://www.dice.com/job-detail/a63fd8f5-ec63-4b60-9935-4b424f7ceb0b ## About the Role 7+ years of software engineering experience, with expertise in backend technologies and AI/ML systems Bachelor's in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or equivalent industry experience) Proven experience building complex agentic systems using LLMs Strong programming skills in Python; proficiency with backend API service development Hands-on experience with Kubernetes and Infrastructure as Code (Terraform) Familiarity with ML concepts including model inference, evaluation, data pipelines, and LLM application development Experience with a cloud data warehouse - Snowflake preferred (warehouses/roles, performance tuning, cost management) Experience developing ELT pipelines and orchestrating transformations (dbt Cloud, Airflow, Dagster, or similar) Strong proficiency in database technologies and CI/CD solutions Excellent communication skills and ability to collaborate with both technical and non-technical teams Experience leading technical projects and mentoring engineers via PR review, collaboration, and ADRs Preferred Qualifications Experience with RAG architectures, prompt engineering, evaluation pipelines, and agentic workflows Familiarity with ML frameworks such as PyTorch, Hugging Face, or LangChain Experience working on platform engineering or developer experience platforms Experience with data engineering practices including dbt, Snowflake, Databricks, and building data marts for analytics Proficiency in JavaScript/TypeScript for tooling and web application development Experience with CQRS/ES architecture patterns Knowledge of observability tools and practices (Telemetry, Prometheus, Grafana) Experience with GitOps workflows and deployment automation Collaborative mindset with keen interest in keeping up with the latest in the industry Ability to work independently on scoped features with minimal supervision ## Description As a Senior AI and Infrastructure Engineer, you will be a hands-on technical leader responsible for designing, building, and supporting AI-powered systems and the infrastructure behind them. You'll develop agentic systems, ML-backed services, and production pipelines while partnering with cross-functional teams to coordinate the complex interdependencies inherent in platform development. This role requires excellent communication skills - you'll collaborate with ESCI subject matter experts from a variety of disciplines to craft requirements, strategy, and architectural patterns that deliver high-impact solutions. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Web APIs you might not know about](https://www.wearedevelopers.com/videos/281-web-apis-you-might-not-know-about) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [All your telemetry data from any source in one place](https://www.wearedevelopers.com/videos/57-all-your-telemetry-data-from-any-source-in-one-place) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)