Staff AI-Native Platform Engineer

Natera • US Remote • 4h ago

Staff AI-Native Platform Engineer (L5)

Location: US - Remote
Experience: 8+ years in Cloud/Platform Engineering or Infrastructure, with a proven track record of leading cross-functional initiatives and influencing organizational AI strategy.

About the Role

We are looking for a visionary Staff AI-Native Platform Engineer to lead the evolution of our technical foundation. In this high-impact role, you will move beyond traditional automation to architect an AI-native ecosystem that integrates Generative AI into every layer of our Development Platform.

As a technical leader within the Platform organization, you won’t just be maintaining infrastructure, you will be reimagining the developer experience (DevEx). You will be the primary advocate for GenAI, fostering a culture of “AI-first” engineering by building agentic workflows that accelerate Cloud Orchestration, CI/CD, Observability, and FinOps. We need a creative engineer who can bridge the gap between cutting-edge LLM capabilities and robust, production-grade platform tooling.

What You’ll Do

Architect AI-Integrated Infrastructure

AI-First Development Platform: Design and build unified interfaces where AI agents manage complex tasks like environment provisioning, automated PR reviews, and self-documenting codebases.
Intelligent Orchestration: Embed AI-driven intelligence into CI/CD pipelines and Observability stacks to enable predictive scaling, automated incident triage, and self-healing systems.
Autonomous FinOps: Evolve AI-assisted FinOps workflows to automate cost attribution, anomaly detection, and optimization recommendations across AWS and other cloud environments.
Governance & Guardrails: Implement AI-driven governance to ensure architectural standards and security policies are met without slowing down developer velocity.

Elevate Developer Experience (DevEx)

Agentic Tooling: Develop production-grade internal tools that use agentic reasoning to solve "day two" operational challenges for product teams.
Internal Developer Portal (IDP): Integrate natural language interfaces into our IDP, allowing developers to interact with the platform through conversational AI.
Actionable Insights: Transform raw telemetry into “executive-ready” insights using advanced data modeling and AI-driven visualization.

Lead AI Mentorship & Evangelism

Strategic Advisory: Partner with senior leadership to model the technical and operational trade-offs of various AI architectural decisions (e.g., Build vs. Buy, Model Selection).
Team Upskilling: Act as a force multiplier by mentoring engineers on advanced AI tooling, prompt engineering for infrastructure, and the deployment of agentic systems.
Community Building: Stay at the forefront of the GenAI landscape, regularly sharing insights and driving the adoption of emerging tools and patterns across the organization.

What You Bring

Platform Expertise: 8+ years of experience in Cloud Engineering (AWS preferred), with deep knowledge of Kubernetes, Terraform/CloudFormation, and modern CI/CD patterns.
AI/ML Applied Logic: Expert-level experience applying AI techniques (summarization, RAG, agentic reasoning) to real-world operational workflows. You understand how to make LLMs "useful" in a production environment.
Advanced Programming: Expert Python skills and experience with AWS SDKs. You are comfortable building complex integrations and custom CLI/API tools.
The "Staff" Mindset: A history of leading large-scale, cross-functional projects. You can navigate ambiguity, build consensus across teams, and deliver measurable business impact.
Creative Evangelism: The ability to present complex AI concepts to both technical and non-technical stakeholders, inspiring teams to shift toward AI-native workflows.
Product Thinking: Experience building Internal Developer Portals (IDP) with a focus on "Platform as a Product" and user-centric design.

Bonus Points

Experience with LangChain, LlamaIndex, or other AI orchestration frameworks.
Contributions to open-source platforms or AI projects.
Experience with vector databases and fine-tuning models for domain-specific tasks.