Principal Machine Learning Engineer

Job summary

The 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 Ora*** Cloud Infrastructure (OCI).

Qualifications

• The ideal candidate combines deep distributed systems experience with practical AI-native engineering, including orchestration of LLMs,
• Bachelor's, Master's, or Ph.
• 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.
• Proven track record as a Staff, Senior Staff, Principal, or equivalent technical leader influencing architecture and execution across multiple teams.
• Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
• Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
• Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
• Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
• Strong programming
• Experience optimizing large-scale GPU inference or training workloads for latency, throughput, utilization, availability, and cost.
• Experience building or operating model serving, inference gateways, agent runtimes, workflow engines, developer platforms, or internal AI productivity platforms.

Responsibilities

• The 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 Ora*** Cloud Infrastructure (OCI).
• 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

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Security clearance