[Remote] Staff Software Engineer, Agentic AI — Nexus

Note: The job is a remote job and is open to candidates in USA. Arlo Technologies, Inc. is dedicated to creating innovative solutions for security technology. They are seeking a Staff Software Engineer to join the Nexus team, focusing on building and expanding agent capabilities for their next-generation chat experience, which integrates with various systems and enhances user interaction through AI-powered agents.ResponsibilitiesDesign and ship new agent capabilities for Nexus — new tools, skills, integrations, and conversational flows that meaningfully expand what users can accomplish through chatBuild and own production-grade Python services (FastAPI, async patterns) that power Nexus's agent runtime, tool execution, and orchestration logicExtend our orchestration layer (LangGraph / LangChain or equivalent) with new agent topologies, routing logic, and tool-use patternsDesign tool-use and function-calling interfaces — including MCP servers — that let Nexus safely interact with Arlo platform APIs, device telemetry, and partner systemsBuild the evals and observability that make agent behavior measurable: offline test suites, online quality metrics, trace tooling, regression detection, and dashboards engineers and PMs actually useOwn the testing strategy for AI experiences — design and build the test harnesses, golden datasets, scenario suites, adversarial/red-team tests, and CI gates that catch agent regressions before they reach users. Define what "good" looks like for conversational quality, tool-use correctness, and task completionPartner closely with product, design, and platform teams to turn user needs into shipped agent features — and bring engineering judgment to scoping, sequencing, and tradeoffsSet technical direction for agent development practices at Arlo: patterns, frameworks, code review standards, and the playbook other engineers follow when they build on NexusMentor mid and senior engineers on LLM systems, prompt design, and production AI engineeringSkills8+ years of software engineering experience, with at least 1-2 years building production LLM-powered systems — ideally agentic chat, copilots, or multi-step agent workflowsStrong production Python — FastAPI, asyncio, type hints, testing discipline. You've built and operated Python services at meaningful scaleHands-on experience with LLM orchestration frameworks like LangGraph, LangChain, LlamaIndex, or equivalent — and an opinion on when to use them vs. build your ownDeep familiarity with tool-use / function-calling patterns. Bonus if you've built or integrated MCP (Model Context Protocol) servers, but strong tool-use experience in any framework translatesExperience designing multi-agent or multi-step workflows: planner/executor patterns, agent handoff, state management, error recovery, human-in-the-loopA real point of view on evals and observability for LLM systems — you've built (or fought to build) the feedback loops that keep agents from regressing in productionHands-on experience testing AI/LLM experiences in production — building eval datasets, scoring rubrics (LLM-as-judge, human-in-the-loop, deterministic checks), regression suites, and the discipline to know which one applies when. You understand why traditional unit tests aren't enough for non-deterministic systems and have built the testing patterns that fill the gapTrack record of shipping at the Staff level — you've operated as a technical leader across teams, not just an individual contributor with a senior title. The bar is delivery and influence, not slide decksExperience with RAG, vector databases, embedding pipelines, and retrieval quality tuningFamiliarity with Anthropic's Claude API, OpenAI's Responses API, or comparable provider SDKs at the level of tool use, structured outputs, and streamingExperience instrumenting LLM systems with tools like LangSmith, Langfuse, Arize, Braintrust, or homegrown tracingExperience with AI testing tooling (Braintrust, Langfuse, Patronus, DeepEval, Promptfoo, or equivalent), or having built homegrown versions of theseFamiliarity with red-teaming, prompt injection testing, or adversarial evaluation of agent systemsExperience building backend systems for IoT or connected devices — reasoning about device state, telemetry streams, intermittent connectivity, command/response patterns, and the kind of real-world messiness that doesn't show up in pure SaaS backends. Bonus if you've designed APIs or agents that operate over a fleet of devicesExperience working with mobile clients (iOS / Android) as API consumers of an agent backendPrior work on prompt engineering at scale, including prompt versioning, A/B testing, and prompt regression frameworksCompany OverviewWe are a passionate and diverse group of thought leaders, creators, and developers across all disciplines dedicated to changing how people protect and connect with the people and things they love. It was founded in 2018, and is headquartered in Carlsbad, California, USA, with a workforce of 201-500 employees. Its website is https://www.arlo.com.Company H1B SponsorshipArlo Technologies, Inc. has a track record of offering H1B sponsorships, with 16 in 2025, 15 in 2024, 9 in 2023, 8 in 2022, 19 in 2021, 6 in 2020. Please note that this does not guarantee sponsorship for this specific role.