Lead Principal AI Software Engineer Oracle
Overview
Senior Staff-level technical leadership role responsible for defining building next-generation AI systems on Oracle Cloud Infrastructure. Sets architecture and engineering direction for production-grade agentic AI platforms autonomous workflows scalable inference infrastructure enterprise AI applications used in large-scale business-critical environments. Requires proven engineer who translates ambiguous product and platform goals into durable technical strategy leads multi-team execution without direct authority remains deeply hands-on in design code reviews operations and incident follow-up.
What You'll Do11
- 1Serve as senior technical owner for OCI AI platform capabilities including agent execution inference systems model serving AI workflow orchestration evaluation and observability
- 2Design 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
- 3Build production-grade services for tool calling agent memory context management Model Context Protocol integration vector retrieval multi-agent coordination policy enforcement and evaluation
- 4Lead architecture across distributed services optimized for low latency high throughput GPU efficiency reliability cost operability and secure multi-tenant operation
- 5Define service boundaries APIs data models state management consistency tradeoffs failure modes SLIs SLOs rollout strategies and operational readiness criteria for AI platform services
- 6Drive technical strategy across infrastructure platform security data and application engineering teams converting broad goals into executable multi-quarter plans and measurable milestones
- 7Integrate AI agents securely and reliably with enterprise APIs cloud services databases identity systems secrets management and external systems
- 8Establish AgentOps and LLMOps practices for tracing monitoring eval suites regression testing experimentation safety guardrails prompt/tool versioning production reliability
- 9Evaluate and operationalize emerging technologies in generative AI agentic workflows inference optimization long-context systems reasoning models AI developer tooling and agentic-first development
- 10Mentor staff and senior engineers raise architectural standards and influence engineering practices across OCI without requiring direct management authority
- 11Own critical production outcomes including reliability performance security posture cost efficiency and supportability for delivered systems
Requirements19
- 1Bachelor's Master's or PhD in Computer Science AI ML Engineering or related field or equivalent practical experience
- 212+ years of professional software engineering experience including significant ownership of production systems or equivalent experience demonstrating Senior Staff Principal impact
- 3Proven track record as Staff Senior Staff Principal or equivalent technical leader influencing architecture and execution across multiple teams
- 4Deep experience designing building operating high-scale distributed systems cloud services infrastructure platforms or AI/ML platform services
- 5Hands-on experience with production AI systems agentic AI applications autonomous workflows tool-using agents multi-step orchestration or multi-agent systems
- 6Practical experience with orchestration frameworks such as LangGraph LangChain CrewAI AutoGen LlamaIndex or similar ecosystems
- 7Deep understanding of LLM application patterns including prompt design structured outputs function/tool calling context management RAG memory tool safety and evaluation
- 8Strong programming skills in Python and ability to contribute high-quality production code reviews tests and debugging in complex distributed environments
- 9Expertise with Kubernetes Docker cloud-native infrastructure service-to-service communication scalability fault tolerance observability and performance analysis
- 10Experience defining SLIs SLOs production readiness criteria incident response practices monitoring tracing experiments and reliability programs for AI or distributed systems
- 11Strong understanding of AI safety governance security and operational risks for autonomous or semi-autonomous systems including data handling access control auditability and human accountability
- 12Excellent written and verbal communication with demonstrated ability to lead technical direction resolve ambiguity and influence senior stakeholders
- 13Preferred Experience optimizing large-scale GPU inference or training workloads for latency throughput utilization availability and cost
- 14Experience building or operating model serving inference gateways agent runtimes workflow engines developer platforms or internal AI productivity platforms
- 15Experience integrating AI systems with enterprise APIs databases cloud services vector databases embeddings retrieval systems identity systems and policy enforcement layers
- 16Experience with LLM fine-tuning long-context systems reasoning models model routing caching batching quantization or emerging generative AI research
- 17Experience building evaluation frameworks for agentic systems including offline evals online experiments golden tasks adversarial testing regression gates and observability dashboards
- 18Experience using AI-assisted software development tools such as Codex Claude Code Cursor Copilot or similar systems in large-scale engineering environments
- 19Track record of defining architectural standards platform capabilities or engineering practices adopted across multiple teams or organizations
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