Senior Principal AI/ML Engineer (OCI)

Salary: $135,200 - 306,400 per year Requirements:

• We require a Bachelors, Masters, or Ph.D. in Computer Science, AI/ML, Engineering, or a related discipline, or equivalent practical experience.
• We require 12+ years of professional software engineering experience, including substantial ownership of production systems, or equivalent Senior Staff / Principal-level impact.
• We require a demonstrated background as a Staff, Senior Staff, Principal, or similar technical leader influencing architecture and delivery across multiple teams.
• We require deep experience designing, building, and operating large-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
• We require practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar tools.
• We require strong knowledge of LLM application patterns, including prompt design, structured outputs, function/tool calling, context handling, RAG, memory, tool safety, and evaluation.
• We require strong programming ability in Python and the capacity to produce high-quality production code, reviews, tests, and debugging in complex distributed environments.
• We require strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
• We require experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experimentation, and reliability programs for AI or distributed systems.
• We require a strong understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
• We require excellent written and verbal communication skills, with the ability to set technical direction, resolve ambiguity, and influence senior stakeholders.
• Preferred experience includes optimizing large-scale GPU inference or training workloads for latency, throughput, utilization, availability, and cost.
• Preferred experience includes building or operating model serving, inference gateways, agent runtimes, workflow engines, developer platforms, or internal AI productivity platforms.
• Preferred experience includes integrating AI systems with enterprise APIs, databases, cloud services, vector databases, embeddings, retrieval systems, identity systems, and policy enforcement layers.
• Preferred experience includes LLM fine-tuning, long-context systems, reasoning models, model routing, caching, batching, quantization, or emerging generative AI research.
• Preferred experience includes building evaluation frameworks for agentic systems, including offline evaluations, online experiments, golden tasks, adversarial testing, regression gates, and observability dashboards.
• Preferred experience includes using AI-assisted software development tools such as Codex, Claude Code, Cursor, Copilot, or similar systems in large-scale engineering environments.
• Preferred experience includes defining architectural standards, platform capabilities, or engineering practices adopted across multiple teams or organizations.
• Preferred experience includes working in enterprise, cloud infrastructure, regulated, security-sensitive, or mission-critical environments.

• We serve as the senior technical owner for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
• We design, architect, and deliver scalable agentic AI systems that support reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
• We build production-ready services for tool calling, agent memory, context management, Model Context Protocol integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
• We lead architecture for distributed services tuned for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
• We define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout plans, and operational readiness standards for AI platform services.
• We drive technical strategy across infrastructure, platform, security, data, and application engineering teams, turning broad objectives into executable multi-quarter plans and measurable milestones.
• We integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
• We establish AgentOps and LLMOps practices for tracing, monitoring, evaluation suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production stability.
• We assess and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
• We strengthen engineering quality through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices.
• We mentor Staff and senior engineers, elevate architectural standards, and shape engineering practices across OCI without relying on direct management authority.
• We own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems we deliver.

• Agentic AI
• AI
• AI Agents
• Architect
• Claude Code
• Cloud
• Copilot
• Cursor
• Docker
• Fine-tuning
• Support
• Kubernetes
• LLM
• Model Serving
• Oracle
• Python
• RAG
• Security
• MCP

More:

We are collaborating with Oracle to connect with exceptional professionals for this Senior Principal AI Agent / ML Software Engineer role. This is a Senior Staff-level, hands-on technical leadership position focused on defining, building, and operating next-generation AI systems on Oracle Cloud Infrastructure. We are seeking someone who can convert ambiguous platform goals into durable technical strategy, lead cross-team execution, and remain deeply involved in design, coding, reviews, operations, and incident follow-up. The role is centered on shipping reliable, secure, observable, and cost-conscious AI platform systems for large-scale, business-critical environments. The posting includes a U.S. hiring range of $135,200 to $306,400 per year, with possible bonus, equity, and compensation deferral, along with a comprehensive U.S. benefits package that includes medical, dental, and vision coverage, disability and life insurance, flexible spending accounts, commuter and parking benefits, a 401(k) with company match, paid time off, paid holidays, paid sick leave, paid parental leave, adoption assistance, employee stock purchase options, financial planning, and group legal support. Career level: IC5.

last updated 37 week of 2026