Senior Software Engineer, Triage Services - Jobs - Careers at Apple
- Architect and lead delivery of the end-to-end agentic triage platform, including agent orchestration, tool integration, data pipelines, and the build and integration lifecycle, with a focus on reliability, latency, and cost at Apple scale.
- Define the evaluation strategy for production agents: offline benchmarks, golden datasets, regression gates, drift detection, and confidence calibration. Set the quality bar for when automation can act without a human.
- Build observability so failures, drift, and low-confidence routing decisions surface before they reach engineers, and turn those signals into measurable improvements.
- Work with Core OS, Hardware, and Silicon engineering leads to find high-leverage automation opportunities, align on requirements, and drive adoption beyond the immediate team.
- Own production agents through their whole life, from prototype to hardened service, including operational excellence and on-call practices for triage-critical infrastructure.
- Mentor and grow engineers in agent design, evaluation methodology, and distributed systems. Raise the technical bar through design reviews and hands-on example-setting.
- 6+ years of software engineering experience building and operating production distributed systems or data platforms at scale.
- Expert-level Python and strong system design skills, with a track record of owning architecture for services other teams depend on.
- 2+ years building and shipping LLM-based or agentic systems to production, including tool calling, orchestration, and guardrails.
- Hands-on experience designing evaluation frameworks for ML/LLM systems, such as offline benchmarks, regression testing, drift detection, and confidence scoring.
- Deep working knowledge of RAG architectures, embedding generation, vector databases, and data preparation for agentic workflows.
- Proven technical leadership: driving multi-quarter projects through ambiguity, influencing across org boundaries, and mentoring other engineers.
- BS in Computer Science or a related field, or equivalent practical experience.
- MS or PhD in Computer Science, Machine Learning, or a related field.
- Background in kernel or OS-level debugging, crash and panic analysis, or root-cause investigation on complex systems.
- Experience with large-scale telemetry or observability systems feeding automated decision-making.
- Track record of shipping platforms or developer tools widely adopted by engineering organizations beyond your own.
- Experience setting technical strategy and roadmaps, and presenting tradeoffs and outcomes to senior engineering leadership.
- Excellent written and verbal communication, including writing design documents that align multiple teams.
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Required Skills
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🇬🇧 English