Network Infrastructure & AI Engineer

Pairwise•Menlo Park, CA

21h•Hybrid

About The Position

At Pairwise, we are a team of engineers, operators, and builders focused on enabling the next generation of technical talent to do their best work. We partner with leading technology companies to deliver high-performance engineering solutions across embedded systems, networking, semiconductors, and software. Our teams have contributed to some of the most advanced products in consumer, infrastructure, and communications technologies. This full-time role offers the chance to work on-site with a global leader in the technology industry, contributing to impactful, technically challenging projects in a high-caliber and fast-moving environment. Overview Join our client's network and infrastructure team in a hybrid role that sits at the intersection of cloud networking and applied AI. You'll spend roughly half your time on network infrastructure and deployment across Azure and AWS, and the other half building the AI platform and agentic applications that run on top of it. Security, compliance, and data privacy are central to everything we ship - you'll be expected to design with those constraints from day one rather than bolt them on later.

Requirements

BS in Computer Science, Electrical Engineering, or a related field with 5+ years of relevant experience; or MS with 2+ years; or PhD with no prior industry experience required.
Hands-on experience with Azure and AWS networking primitives (VNets/VPCs, peering, private endpoints, hybrid connectivity).
Strong Python skills for AI application development.
Production experience with infrastructure-as-code (Terraform, Bicep), Kubernetes, and CI/CD for both infra and ML workloads.
Experience building or operating RAG and/or agentic systems, with exposure to LangGraph, LangChain, or comparable frameworks.
Demonstrated ability to operate independently in ambiguous environments - scoping vague problems, sequencing the work, and driving to a result without close direction.

Nice To Haves

Direct exposure to the telecom domain: mobile network operators, RAN/core architecture, 4G/5G, or working with OEM network equipment vendors.
Experience designing systems under strict security and compliance constraints.
Familiarity with observability for LLM applications: tracing, evals-as-CI, and cost/latency monitoring.

Responsibilities

Design and operate cloud network infrastructure on Azure and AWS, including VNets/VPCs, peering, private connectivity, and segmentation.
Own the infrastructure-as-code, Kubernetes, and CI/CD pipelines that deliver both our network footprint and our ML workloads.
Build and run the platform that hosts our AI workloads: model gateways, vector stores, ingestion pipelines, and deployment plumbing.
Develop RAG workflows end-to-end and implement agentic features using LangGraph and LangChain.
Build and run evaluations for AI quality so changes ship with confidence rather than vibes.