Principal Core Infrastructure Engineer - AI-Powered Digital Twin Platform

hackajob is collaborating with Oracle to connect them with exceptional professionals for this role.

Description

Oracle is seeking a Principal Software Developer to help design and build an AI-powered Digital Twin platform. The platform will combine real-time operational data, digital models, simulation, graph technologies, and AI agents to help customers understand complex systems, predict outcomes, investigate issues, and automate actions safely.

This is a senior individual contributor role for an engineer who can lead complex technical initiatives, influence architecture across teams, and deliver production-grade capabilities spanning distributed systems, data platforms, generative AI, and agentic workflows.

Responsibilities

Responsibilities

• Design and build scalable services for digital models, telemetry, state management, relationships, simulation, and real-time analytics.
• Develop AI agents that reason over digital twin data, enterprise knowledge, telemetry, and operational systems.
• Build capabilities for RAG, graph-based retrieval, agent orchestration, tool use, memory, evaluation, and human approval.
• Define technical designs and influence architecture across multiple components and engineering teams.
• Develop secure, reliable, and observable distributed systems for enterprise cloud environments.
• Ensure AI-generated recommendations and actions are grounded, explainable, auditable, and policy-compliant.
• Partner with product managers, applied scientists, architects, and engineers to convert customer requirements into scalable platform capabilities.
• Lead complex feature development from design through implementation, testing, deployment, and production support.
• Improve engineering quality through design reviews, code reviews, automated testing, operational readiness, and technical mentoring.
• Investigate and resolve difficult performance, reliability, data consistency, and production issues.

Qualifications

• 8+ years of software engineering experience building large-scale production systems.
• Strong programming skills in Java, Python, Go, C++, or a comparable language.
• Deep understanding of distributed systems, data structures, algorithms, APIs, databases, and cloud architecture.
• Experience designing and operating highly available, multi-tenant cloud services.
• Experience with generative AI, large language models, RAG, AI agents, or agentic orchestration.
• Familiarity with graph databases, vector search, event streaming, time-series data, or simulation systems.
• Experience delivering complex projects across multiple services or teams.
• Strong debugging, problem-solving, and system-design skills.
• Ability to communicate technical decisions clearly and influence without direct authority.

Preferred Qualifications

• Experience with digital twins, IoT, industrial systems, cloud operations, or simulation platforms.
• Experience with Lang Graph, Lang Chain, Llama Index, Semantic Kernel, OCI Generative AI Agents, or similar technologies.
• Knowledge of LLMOps, agent evaluation, prompt and policy versioning, model monitoring, and AI governance.
• Experience building knowledge graphs, hybrid retrieval systems, or enterprise RAG solutions.
• Experience applying AI agents to root-cause analysis, predictive maintenance, optimization, incident response, or automated remediation.
• Experience with OCI, Oracle Database, Kubernetes, graph databases, streaming platforms, or vector databases.
• Experience mentoring engineers and providing technical leadership for major platform initiatives.

Key Responsibilities
System Design & Architecture - System Scalability:
-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.
-Optimize code and/or systems for large-scale data processing and high-throughput requirements to support hyper-scale systems.
-Define scalability requirements for owned components and ensure design and implementation requirements are met.
-Design systems to scale with elasticity (e.g., effectively scaling both up and down).
-Leverage data plane platforms to effectively handle large-scale data retrieval, storage, and processing.
-Design performance and load testing.

System Design & Architecture - System Reliability Design:
-Build and design fault-tolerant components and systems capable of withstanding in-service updates by implementing redundancy, replication, and automatic failover mechanisms.
-Design systems to effectively handle service disruptions (e.g., network partitions) by prioritizing consistency, availability, or partition tolerance.
-Implement and optimize approaches to handle network unreliability, including load-shedding, throttling, and rate-limiting.
-Design components and systems that are durable and adhere to service level objectives (SLOs), setting expectations for availability and durability of other computing services within the department.

System Design & Architecture - System…