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Senior Principal AI Agent​/ML Software Engineer; OCI

Job in Seattle, King County, Washington, 98127, USA
Listing for: Oracle
Full Time position
Listed on 2026-05-27
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Cloud Engineer - Software, Senior Developer
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
Position: Senior Principal AI Agent / ML Software Engineer (OCI)

Job Description

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
  • 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 Agent Ops and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
  • Evaluate and ope rationalise emerging technologies in generative AI, agentic workflows, inference optimisation, 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 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,…
Position Requirements
10+ Years work experience
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