Job Overview
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Job Description
Summary
Full-stack builders, come join a creative engineering team devoted to making our products more durable through data-driven insights. We're looking for a Senior Software Engineer, Applied AI to lead the development of intelligent applications and systems that unlock the power of our hardware test data and enable hardware engineers to create their own software tools. In this role, you'll architect and build scalable software to help take our department's capabilities to the next level. You'll work with hardware and software engineering teams throughout Apple to design robust AI/ML applications, implement production-grade software and AI pipelines, iterate based on evolving requirements, and provide input on technical strategy. The tools and platforms you build will power processes, analytics, and workflows that directly influence the design of future products. This is a hands-on work environment where engineers are expected to be self-motivated and proficient with a wide range of AI/ML technologies, while dedicating time to leading contractors, driving projects forward, presenting to executive leadership, and delivering excellent solutions for Apple.
Description
In this role you'll architect and implement AI/ML software applications at cloud-scale for the Reliability department at Apple. You’ll provide technical leadership and bridge the gap between business needs and production software, delivering tools that automate workflows and surface novel insights for the organization.
Responsibilities
- Architect and build robust, full-stack GenAI-oriented applications using modern software engineering best practices, including a Python/FastAPI backend, a React/Next.js TypeScript frontend, AWS RDS and ElastiCache data stores, and containerized deployments on AWS EKS with Helm and Terraform, while providing technical leadership across projects.
- Extend and maintain a multi-tenant EKS platform that enables users to build, deploy, and run their own applications in Kubernetes pods, with integrated build pipelines, sidecars, and session-affinity reverse proxy at 5,000+ pod scale.
- Design and integrate GenAI capabilities into the platform, including agentic workflows, AI agent skills, LLM-powered web features, and production-grade inference pipelines.
- Drive the scope of engineering projects independently, identifying new opportunities, defining requirements, and managing the full project lifecycle from concept to deployment.
- Lead and mentor a team of external contractors, providing architectural guidance, code reviews, and daily direction to ensure fast, high-quality delivery.
- Implement and operate production observability with OpenTelemetry tracing, Prometheus metrics, and structured logging to ensure application reliability and performance.
- Cultivate strong partnerships across engineering and business teams, acting as both a visionary and translator between software and non-software audiences.
- Act as the primary point of contact for stakeholders, tailoring communication to multidisciplinary audiences while delivering regular updates on project roadmaps.
- Present complex technical narratives and data-driven insights effectively to executive leadership through clear, high-impact presentations and visualizations.
Minimum Qualifications
- B.S. in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related field.
- 6+ years software engineering experience with strong foundation in CS fundamentals, including data structures, algorithms, and proficiency building production web applications using Python (FastAPI, SQLAlchemy), TypeScript (React/Next.js), and cloud-scale containerized services on Kubernetes (EKS, Helm, Terraform).
- 2+ years experience with applied AI Engineering, building software leveraging GenAI and ML to create production-level solutions to business needs, and enhance organizational and development workflows.
- Demonstrated leadership experience with the ability to lead contractors, mentor peers, and manage technical resources effectively.
- Proven ability to drive projects independently: defining scope, collaborating with stakeholders, negotiating requirements, and driving projects to completion.
- Excellent communication and presentation skills, with the ability to articulate complex technical concepts to diverse audiences and influence decision-making while thriving in a fast-paced, evolving environment.
Preferred Qualifications
- M.S. in Computer Science, Software Engineering, Computer Engineering, Machine Learning, or related field.
- Passion for quality and attention to detail; proactive in researching and assessing emerging technologies (AI/ML models, protocols, and techniques), and integrating them into production.
- Deep expertise in Kubernetes networking (NetworkPolicies, ingress, service mesh, sidecars, pod-to-pod TLS), particularly in enterprise environments with corporate proxies and WAFs.
- Strong experience building multi-tenant platforms that execute user-submitted code, including container image builds, workload isolation, RBAC systems, and secure callback architectures.
- Experience building or integrating agentic AI systems, LLM tool-use patterns, or AI-assisted development workflows.
- Experience with production observability stacks: OpenTelemetry, Prometheus, structured logging, distributed tracing, and dashboarding tools such as Grafana.
- Track record of successfully growing the scope of engineering projects from initial proof-of-concept to organization-wide adoption.
- 6+ years experience and strong foundation in Software Engineering fundamentals, including data structures, algorithms, object-oriented design, and proficiency in building production-quality applications.
- Experience with computer vision technologies and techniques, especially for segmentation, anomaly detection, and objective grading is a plus.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $302,200, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
Apple accepts applications to this posting on an ongoing basis.
Key skills/competency
- Applied AI Engineering
- Full-stack Development
- Generative AI (GenAI)
- Kubernetes (EKS)
- Python/FastAPI
- React/Next.js
- Cloud-scale Applications
- Technical Leadership
- Observability (OpenTelemetry, Prometheus)
- Project Management
How to Get Hired at Apple
- Research Apple's culture and values: Study their commitment to innovation, quality, and impact. Understand how your contributions align with Apple's mission.
- Tailor your resume for applied AI engineering: Highlight experience with GenAI, full-stack development, and cloud-scale AI/ML solutions, specifically Python, React, and Kubernetes.
- Showcase technical leadership and project ownership: Provide examples where you've led projects, mentored teams, and driven technical strategy from conception to deployment.
- Prepare for in-depth technical discussions: Be ready to discuss data structures, algorithms, distributed systems, and your specific experience with AWS EKS, Helm, Terraform, and observability tools.
- Practice articulating complex insights: Refine your ability to present technical narratives and data-driven findings effectively to diverse audiences, including executive leadership.
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