Senior Software Engineer, Environment and Supply Chain Innovation

The Environment and Supply Chain Innovation (ESCI) team sits within Worldwide Operations and works to uphold Apples values across our global supply chain. The ESCI Technology Solutions team is seeking an experienced AI and infrastructure engineer to join us. Youll work alongside other software and data engineers in collaboration with our internal and external users to build applications that help support ESCIs goals which include upholding the highest standards of labor and human rights for the people in our supply chain and Apple 2030 Apples goal to be carbon neutral across our global footprint by 2030.

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. Youll 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 youll collaborate with ESCI subject matter experts from a variety of disciplines to craft requirements strategy and architectural patterns that deliver high-impact solutions.

Design and build complex agentic systems using LLMs including RAG pipelines prompt engineering evaluation frameworks and inference endpointsnDevelop and maintain backend services supporting ML workloads data ingestion model evaluation and production inferencenDesign and maintain cloud infrastructure (Kubernetes Terraform) to support AI workloads and application deploymentsnWrite well-tested production-ready code with attention to reliability performance and developer experiencenSupport the data engineering team with scalable infrastructure for ELT pipelines and data warehousingnContribute to observability monitoring dashboards and tooling for ML systemsnCollaborate with cross-functional teams to translate business requirements into technical solutions and strategiesnParticipate in design reviews code reviews and establish engineering best practices via ADRs and knowledge sharingnCommunicate and present technical solutions strategy and roadmaps to ESCI stakeholders and leadership

7 years of software engineering experience with expertise in backend technologies and AI/ML systemsnBachelors in Computer Science Artificial Intelligence Machine Learning or a related field (or equivalent industry experience)nProven experience building complex agentic systems using LLMsnStrong programming skills in Python; proficiency with backend API service developmentnHands-on experience with Kubernetes and Infrastructure as Code (Terraform)nFamiliarity with ML concepts including model inference evaluation data pipelines and LLM application developmentnExperience with a cloud data warehouse Snowflake preferred (warehouses/roles performance tuning cost management)nExperience developing ELT pipelines and orchestrating transformations (dbt Cloud Airflow Dagster or similar)nStrong proficiency in database technologies and CI/CD solutionsnExcellent communication skills and ability to collaborate with both technical and non-technical teamsnExperience leading technical projects and mentoring engineers via PR review collaboration and ADRs

Experience with RAG architectures prompt engineering evaluation pipelines and agentic workflowsnFamiliarity with ML frameworks such as PyTorch Hugging Face or LangChainnExperience working on platform engineering or developer experience platformsnExperience with data engineering practices including dbt Snowflake Databricks and building data marts for analyticsnProficiency in JavaScript/TypeScript for tooling and web application developmentnExperience with CQRS/ES architecture patternsnKnowledge of observability tools and practices (Telemetry Prometheus Grafana)nExperience with GitOps workflows and deployment automationnCollaborative mindset with keen interest in keeping up with the latest in the industrynAbility to work independently on scoped features with minimal supervision