2 months ago
Cork, IrelandStaff+
Responsibilities
- Design, build, and operate shared AI platform infrastructure covering model routing, fallback strategies, API gateways, rate limiting, and multi-provider abstractions.
- Optimise AI costs and usage through model selection, prompt and context efficiency, caching, and session-level controls.
- Build evaluation, observability, monitoring, regression detection, and usage analytics for LLM-powered features and agents.
- Define secure and scalable AI integration architecture, including authentication, data handling, and compliance considerations.
- Drive adoption of AI coding agents and assistants across engineering teams and build related tooling, guardrails, and workflows.
- Establish AI engineering best practices, documentation, training, and developer enablement programs.
- Partner with business and corporate functions to simplify workflows and design AI solutions, agents, connectors, and internal applications.
- Create reusable enablement patterns, templates, onboarding materials, office hours, and a cross-functional community of practice.
- Own end-to-end initiatives, conduct architecture and code reviews, debug platform systems, and mentor engineers and functional champions.
- Set objectives, measure outcomes, and report on AI-driven productivity gains and cost efficiency.
Requirements
- 8+ years of software engineering experience with a history of leading impactful technical initiatives.
- Hands-on production experience with LLM APIs such as Anthropic or OpenAI, including prompt and context design, tool use, and agentic workflows.
- Experience simplifying complex business or legacy processes into reliable, automatable solutions.
- Experience working directly with non-technical stakeholders to deliver technology they adopt and continue using.
- Strong cost, performance, and reliability optimisation experience in cloud or distributed systems.
- Experience building or operating internal developer platforms, APIs, or shared infrastructure used by multiple teams.
- Practical experience with AI-assisted development tools and scaling their use across an organisation.
- Strong distributed-systems, observability, secure API design, architecture, and technical communication skills.
- Proficiency in Python, JavaScript, TypeScript, or similar platform and tooling languages.
- Experience defining and delivering platform or enablement strategies rather than only individual features.
- 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: experience in business-process automation, RPA, workflow tooling, enterprise systems integration, CI/CD and DevOps automation, cloud platforms and cloud-native architectures, data or ML engineering, evaluation frameworks, LLMOps, and mobile, web, or embedded systems.
Benefits
- Hybrid work arrangement based in the NETGEAR Cork office.
- Significant autonomy and the opportunity to influence organisation-wide AI strategy and measurable business outcomes.
- Mentorship, cross-functional collaboration, and participation in a culture focused on technical excellence and responsible AI use.
Tech Stack
Categories
About NETGEAR
NETGEAR builds consumer and SMB networking hardware and services—Wi‑Fi routers and mesh systems, Ethernet switches, modems, and network-attached storage—with cloud management and security subscriptions. It sells through retail, online, and channel partners, and works with internet service providers. Founded in 1996 and headquartered in San Jose, California, NETGEAR is a public company traded on NASDAQ (NTGR) with global distribution across home, business, and service-provider markets.