Principal Core Infrastructure Software Engineer

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Description

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.

Responsibilities

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 Lang Graph, Lang Chain, CrewAI, Auto Gen, Llama Index, or similar ecosystems.
Deep understanding of LLM application patterns, including prompt design, structured outputs,…