Lead Principal Machine Learning Engineer

The Senior Principal AI Agent / ML 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). The Senior Principal AI Agent / ML 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 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 **Responsibilities** - Serve as a senior technical owner for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability. - 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. - Build production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation. - Lead architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation. - Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services. - Drive technical strategy across infrastructure, platform, security, data, and application engineering teams, converting broad goals into executable multi-quarter plans and measurable milestones. - Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems. - Establish AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability. - Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development. - Drive engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems. - Mentor Staff and senior engineers, raise architectural standards, and influence engineering practices across OCI without requiring direct management authority. - Own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered. **Required Qualifications** - Bachelor's, Master's, or Ph.D. in Computer Science, AI/ML, Engineering, or a related field, or equivalent practical experience. - 12+ years of professional software engineering experience, including significant ownership of production systems; or equivalent experience demonstrating Senior…