Role Overview

This is a hybrid role based in our Cork office.

As a Staff Engineer on NETGEAR’s AI Platform and Enablement team, you will play a strategic and highly impactful role in shaping how AI is built into the fabric of the whole company: engineering teams, business units and corporate functions alike. This position is designed for a deeply experienced technical leader who thrives at the intersection of AI infrastructure, developer enablement and business enablement.

You will own three interconnected areas of ownership. First, you will help build and operate the core AI and LLM platform: model routing, evaluation, and the shared tooling that lets teams across NETGEAR build reliably on top of large language models. Second, you will scale the use of coding agents and assistants across engineering, raising AI fluency and the bar on how we ship software. Third, and equally important, you will extend AI enablement beyond engineering and into business functions — finding the workflows worth automating and building them.

That third mandate is not a side project. A meaningful share of NETGEAR’s near-term AI value sits in business process, not product code, and this role is expected to have organisation-wide impact. Much of the work will resemble the enablement currently being driven for non-technical teams, scaled up and made repeatable.

With significant autonomy, you will own delivery of key technical initiatives aligned with organisational goals and directly influence the short and medium-term success of NETGEAR’s AI strategy.

Key Responsibilities

AI and LLM Platform Infrastructure

Design, build, and operate the shared AI platform layer: model routing and fallback strategies, API gateway patterns, rate limiting, and multi-provider abstraction (Anthropic, OpenAI, and others as needed).
Own cost and usage optimisation across the organisation’s AI spend, covering model selection, prompt and context efficiency, caching, and session-level cost controls.
Build evaluation, observability, and monitoring for LLM-powered features and agents, including quality regression detection and usage analytics.
Define architecture and standards for secure, scalable integration of AI capabilities into product and internal systems, including authentication, data handling, and compliance considerations.

Engineering AI Enablement

Drive adoption and effective use of AI coding agents and assistants (for example Claude Code, GitHub Copilot, Cursor) across engineering teams.
Build internal tooling, guardrails, and workflows (agentic SDLC patterns, managed agents, review and QA processes) that let engineers safely delegate more work to AI.
Establish best practices, documentation, and training that raise the AI fluency of the wider engineering organisation.

Business and Functional Enablement

Partner directly with business units and corporate functions (Finance, Operations, Supply Chain, Marketing, Sales, People, Legal) to identify high-value AI opportunities in their day-to-day work.
Sit with functional teams, map how their processes actually run today, and simplify before automating: strip out steps that exist only for historical reasons rather than encoding them into an agent.
Design and deliver AI solutions for non-technical users, including skills, agents, connectors and internal applications that people without an engineering background can adopt and trust.
Build the enablement layer that makes this repeatable: reusable patterns, templates, onboarding material, office hours, and a community of practice across functions.
Translate fluently in both directions - turning business problems into technical designs and explaining technical constraints and risks in language a functional leader can act on.

Technical Leadership and Collaboration

Reporting directly to the AI Platform Engineering Director, working with cross-functional teams to align technical execution with NETGEAR’s AI strategy.
Own delivery of end-to-end initiatives that bridge platform infrastructure, developer tooling, business process and product engineering.
Conduct architecture reviews, code reviews, and system debugging across multiple layers of the platform.
Provide mentorship and guidance to engineers and functional champions working with AI tools and platform services, nurturing a culture of technical excellence and responsible AI use.
Establish and track clear objectives, delivering measurable results aligned with quarterly goals and reporting on AI-driven productivity gains and cost efficiency across the organisation.

Required Qualifications

8+ years of software engineering experience, with a demonstrated history of leading impactful technical initiatives.
Hands-on experience building with LLM APIs (Anthropic, OpenAI, or similar) in production, including prompt and context design, tool use, and agentic workflows.
Demonstrated ability to simplify complexity: taking a tangled business flow or legacy process, understanding it end to end, and reducing it to something clear, reliable and automatable. A track record of continuously exploring new tools and techniques in a fast-moving field.
Experience working directly with non-technical stakeholders to deliver technology that they adopt and keep using.
Strong track record of cost, performance, and reliability optimisation in cloud or distributed systems, with a proven ability to influence business outcomes through technology decisions.
Experience building or operating internal developer platforms, APIs, or shared infrastructure used by multiple teams.
Practical experience with AI-assisted development tools and a genuine interest in scaling their use across an organisation.
Strong design and architectural skills, including experience with distributed systems, observability, and secure API design.
Proficiency in one or more of: Python, JavaScript, TypeScript, or similar languages used for platform and tooling development.
Demonstrated experience defining and delivering on a platform or enablement strategy, not just individual features.
Strong communicator, able to articulate technical direction to both technical and non-technical audiences and comfortable presenting to functional leadership.
Experience with agent frameworks, MCP (Model Context Protocol), or similar tool-orchestration approaches.
Bachelor’s degree in Computer Science or equivalent hands-on experience.

Preferred Qualifications

Background in business process automation, RPA, workflow tooling or systems integration across enterprise applications (for example ERP, CRM, finance or supply chain systems).
Expertise with CI/CD, DevOps practices, and automation (for example GitHub Actions) applied to AI and ML workflows.
Experience with cloud platforms (AWS preferred) and cloud-native architectures.
Background in data or ML engineering, evaluation frameworks, or LLMOps.
Experience working across mobile, web, or embedded systems and understanding how AI integrates with each.

Company Statement/Values:

At NETGEAR, we are on a mission to unleash the full potential of connectivity with intelligent solutions that delight and protect. We turn ideas into innovative networking products that connect people, power businesses, and advance the way we live.

We're a performance-driven, talented and connected team that's committed to delivering world-class products for our customers. As a company, we value our employees as the most essential building blocks of our success. And as teammates, we commit to taking our work to the Next Gear by living our values: we Dare to Transform the future, Connect and Delight our customers, Communicate Courageously with each other and collaborate to Win It Together. You’ll find our values woven through our processes, present in our decisions, and celebrated throughout our culture.

We strive to attract top talent and create a great workplace where people feel engaged, inspired, challenged, proud and respected. If you are creative, forward-thinking, passionate about technology and are looking for a rewarding career to make an impact, then you've got what it takes to succeed at NETGEAR. Join our network and help us shape the future of connectivity.

NETGEAR hires based on merit. All qualified applicants will receive equal consideration for employment. All your information will be kept confidential according to EEO guidelines.

Staff Engineer - AI Platform and Enablement

Benefits

Job Description