Senior Software Engineer Enterprise Technology Services

Apple•Sunnyvale, CA

About The Position

Apple’s Information Systems and Technology (IS&T) organization is seeking a Senior Software Engineer to help transform business processes using generative AI, agentic AI, workflow orchestration, and process automation. The role partners closely with business functions to understand their workflows and pain points, design scalable production solutions, and measure the business impact of those solutions. The engineer will tailor AI and automation platforms to business environments; deploy and operationalize AI agents, LLM-powered workflows, and complex data models; and integrate them with enterprise systems and APIs. The role also establishes automation operating models and governance, develops reusable frameworks, and builds evaluation, monitoring, logging, alerting, and cost-tracking capabilities for production AI workflows. Solutions must meet privacy, security, compliance, and responsible AI standards, including appropriate data handling, access controls, and human-in-the-loop safeguards. This position works across engineering, IT, operations, and business teams to troubleshoot deployments, guide stakeholders with data-driven insights, oversee vendor performance, and support change management, training, and adoption. It also measures outcomes such as hours saved, cycle time, error rates, adoption, and ROI; shares product feedback with internal development teams; evaluates emerging technologies; and mentors engineers while promoting engineering best practices.

Requirements

At least 6 years of experience in application development, with a proven track record of building highly reliable and scalable systems.
Strong proficiency in Java and/or Python, with understanding of object-oriented techniques, algorithms, design patterns, and reusable component design.
Hands-on experience building generative AI solutions, including LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, tool/function calling, embeddings, and vector databases.
Proven experience tailoring generative AI and process automation platforms to complex business environments.
Experience designing APIs and integrating with enterprise systems, such as REST services, event-driven architectures, ERP, CRM, or ITSM platforms.
Experience with cloud platforms, containerization, and CI/CD.
Strong analytical, problem-solving, and troubleshooting skills.
Experience as a technical thought leader who influences leadership decisions through data-driven insights and executive storytelling.
Bachelor’s or master’s degree in Computer Science, Software Engineering, or equivalent experience.

Nice To Haves

Experience building agentic AI solutions, including agent frameworks and protocols such as LangGraph and MCP, and multi-agent orchestration.
Experience with workflow orchestration or process automation platforms such as Temporal, Airflow, Camunda, UiPath, or ServiceNow.
Familiarity with LLMOps/MLOps practices, including model versioning, evaluation pipelines, and guardrails.
Experience with process mining or process discovery tools.
Track record of taking AI automation from proof of concept to scaled production.
Good understanding of relational and NoSQL database technologies.
Commitment to delivering high-quality code with unit and integration tests.
Hands-on experience with Agile methodologies.
Passion for the customer and user experience, and willingness to act on user feedback.
Excellent prioritization and scheduling skills, and ability to handle ambiguity.
Attention to detail and ability to learn new applications and technologies quickly.
Ability to thrive collaboratively within the team and across groups.
Passion for operational excellence and clear communication with cross-functional teams.

Responsibilities

Customize generative AI and process automation platforms for individual business-function environments.
Deploy and operationalize AI agents, LLM-powered workflows, and complex data models in production, integrating them with enterprise systems and APIs.
Define and establish an automation operating model, including intake, prioritization, delivery standards, governance, and support handoff.
Build reusable components, templates, and patterns to scale automation across business functions.
Design evaluation frameworks to assess accuracy, reliability, hallucination rates, and drift in generative AI and agentic solutions.
Build monitoring, logging, alerting, and cost-tracking capabilities for production AI workflows.
Ensure solutions comply with privacy, security, compliance, and responsible AI standards, including data handling, access controls, and human-in-the-loop safeguards.
Troubleshoot complex technical blockers and debug deployment issues, serving as a liaison between business functions and product engineering.
Work alongside business functions to understand workflows, pain points, and automation opportunities.
Define and track success metrics, including hours saved, cycle time reduction, error rates, adoption, and ROI.
Influence senior leadership decisions through data-driven insights and executive storytelling.
Lead global cross-functional initiatives across engineering, IT, and operations, and manage vendor performance to deliver projects on time, within budget, and with high quality.
Partner with business teams on user adoption, training, and change management.
Relay customer insights to internal development teams to improve the core platform.
Evaluate emerging technologies, including agentic AI, LLMs, and cloud-native services, to improve efficiency and reliability.
Mentor engineers and promote engineering best practices through code reviews and design reviews.