Principal Core Infrastructure Software Engineer

The Principal Core Infrastructure Software Engineer is a Senior Staff-level, hands-on technical leadership role responsible for defining, building, and operating next-generation AI systems on Oracle Cloud Infrastructure (OCI). This person will set architecture and engineering direction for production-grade cloud distributed systems, agentic AI platforms, autonomous workflows, scalable inference infrastructure, and enterprise AI applications used in large-scale, business-critical environments.

This role requires a proven engineer who can translate ambiguous product and platform goals into durable technical strategy, lead multi-team execution without direct authority, and remain deeply hands-on in design, code, reviews, operations, and incident follow-up. The ideal candidate combines deep distributed systems experience with practical AI-native engineering, including orchestration of LLMs, tools, APIs, memory, retrieval, evaluation, guardrails, and cloud services. The expectation is to ship, scale, and operate reliable, secure, observable, and cost-aware AI platform systems while raising the technical bar for engineers across the organization.

Key Responsibilities include:

• Lead the development and implementation, and begin to architect, components of scalable distributed systems that support horizontal and vertical scaling to meet system demands, including leveraging distributed state management tools.
• Design, architect, and deliver scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
• Define scalability, performance, availability, and durability requirements for owned services and components.
• Build fault-tolerant systems that support redundancy, replication, automated failover, and in-service upgrades.
• Optimize services for high-throughput, low-latency, and large-scale cloud workloads.
• Design systems that handle network unreliability, service disruptions, and partition scenarios while meeting SLOs.
• Establish telemetry, KPIs, dashboards, and alerts to monitor service health, performance, reliability, and customer impact.
• Drive performance testing, load testing, fault injection, brownout testing, and other validation strategies to ensure correctness and resiliency.
• Implement secure infrastructure controls for multi-tenant cloud environments, including access controls, encryption, and remediation of security gaps.
• Develop automation, Infrastructure as Code, and deployment tooling to support safe patching, updates, rollbacks, and operational recovery.
• Take ownership of production operations, including troubleshooting, incident response, root cause analysis, and ongoing service improvements.
• Strengthen operational readiness by improving runbooks, monitoring, change management, deployment safety, and recovery processes.
• Collaborate with partner teams across OCI to align architecture, dependencies, and service requirements.
• Mentor engineers, review technical designs, guide implementation decisions, and help raise the engineering bar across the team.

Required Qualifications:

• Bachelor's, Master's, or Ph.D. in Computer Science, AI/ML, Engineering, or a related field, or equivalent practical experience.
• 6-10+ years of professional software engineering experience, including significant ownership of production systems; or equivalent experience demonstrating Senior Staff / Principal-level impact.
• Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
• Strong programming skills in Java or Golang or Python and ability to contribute high-quality production code, reviews, tests, and debugging in complex distributed environments.
• Strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
• Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
• Software Estimation: Demonstrated ability to provide accurate software effort and complexity estimates for project planning and scheduling.
• Agile Methodologies: Demonstrated ability to use agile methodologies to drive continuous improvement and product delivery
• Excellent written and verbal communication, with demonstrated ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.

Preferred Qualifications:

• Experience with large scale cloud platforms (e.g., AWS, Azure, Google, Oracle Cloud).
• Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
• Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
• Experience using AI-assisted software development tools such as Codex, Claude Code, Cursor, Copilot, or similar systems in large-scale engineering environments.
• Experience in enterprise, cloud infrastructure, regulated, security-sensitive, or mission-critical environments.