Principal Software Engineer (Agentic AI)

Oracle

About The Position

The SaaS Observability organization oversees all enterprise software services supporting over 25,000 customers and processing more than 60 billion transactions daily. Within this group, the Observability team delivers strategic software solutions and large-scale production engineering services that ensure our cloud products operate with maximum reliability, performance, and resilience. SaaS Observability operates one of the largest telemetry infrastructures in the industry, handling petabytes of data, monitoring billions of objects, and maintaining modern telemetry pipelines across distributed environments. The team is actively advancing its Agentic AI infrastructure to enable intelligent, autonomous observability. We’re seeking a visionary Principal Software Engineer – Agentic AI to lead the evolution of our observability platform into an intelligent, agentic AI-powered system. You’ll architect scalable solutions that integrate telemetry, LLMs, and autonomous agents to deliver predictive insights, automated diagnostics, and real-time decision support across our global cloud infrastructure. This role sits at the intersection of enterprise AI, cloud observability, and multi-agent orchestration, ideal for a technical leader who thrives on innovation, scale, and strategic impact. This role blends deep architectural expertise with engineering leadership to drive the design, development, and enterprise adoption of a modular Agentic AI modular framework for observability. You will lead cross-functional teams, shape technical strategy, and influence product direction across cloud-native environments. Your mission: build intelligent, autonomous systems that transform telemetry into actionable insights securely, scalably, and intuitively.

Requirements

Deep experience with Large Language Models (LLMs), with hands-on implementation of intelligent workflows on equivalent frameworks.
Proven track record in designing agentic AI systems, multi-agent orchestration, and LLM-based automation for enterprise-grade use cases.
Proficient in Retrieval-Augmented Generation (RAG) architectures, vector database integration, and advanced prompt engineering for scalable, context-aware AI solutions.
Extensive experience with modern observability stacks, including Grafana, Prometheus, Loki, Tempo, and Open Telemetry.
Skilled in large-scale implementation, service integration, and architecting telemetry pipelines across multi-cloud environments (OCI, AWS, Azure) with a focus on reliability, scalability, and performance.
Proven ability to lead AI/ML initiatives, including capabilities like predictions and anomaly detections, and operational integration.
Strong proficiency in Python, microservices architecture, containerization (Docker/Kubernetes), API design, CI/CD pipelines, and event-driven systems.
Adept at building iterative diagramming, and crafting executive-level presentations.
Skilled in stakeholder engagement and cross-functional alignment across engineering, product, and leadership teams.
Bachelor’s degree in computer science, Engineering, or a related technical field.
10+ years of experience in cloud architecture, observability platforms, or enterprise AI systems.
5+ years in technical leadership or principal architect roles.

Nice To Haves

Master’s or PhD in Computer Science, AI, or Systems Engineering
Published thought leadership in AI observability or autonomous infrastructure.
Experience mentoring senior engineers, architects, and building high-impact technical teams.

Responsibilities

Architect and implement agentic AI frameworks for observability tooling stack on Oracle Cloud Infrastructure.
Design and operationalize Retrieval-Augmented Generation (RAG) pipelines and vector database integrations.
Lead the transformation of observability systems using Grafana, Prometheus, Loki, Tempo, and Open Telemetry across multi-cloud environments (OCI, AWS, Azure)
Drive AI/ML initiatives from concept to deployment, including predictive analytics, time-series modeling, and statistical inference.
Collaborate with engineering, product, and executive teams to align technical solutions with business goals.
Deliver roadmap, architecture diagrams, and executive-level presentations to communicate complex systems with clarity.
Mentor cross-functional teams and contribute to strategic hiring for AI and observability talent.