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# Staff Software Engineer - AI

- **Company:** Luxer One
- **Location:** Carlsbad, CA, United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Software, Microsoft Outlook, Data Integration, Software Debugging, Zoho Office Suite, Facebook Ads Manager, Enterprise Software Applications, Retrieval-Augmented Generation, Multi-Agent Systems, Prompt Engineering, Backend, Kubernetes, Slack, Invoking Functions, Model Context Protocol
- **Published:** October 20, 2026
- **Apply:** https://www.juju.com/job/23_F3F8EA738331C73011C4D44E56D1F1AD

## About the Role

They learn the work, find the highest-leverage opportunities, and ship agentic AI systems that change how the business operates - measured by outcomes, not activity.Who You Are: You are an engineer who is equally at home debugging an integration and presenting ROI to a GM. You move fast, operate independently, and measure your work by what changed in the business - not by lines of code shipped.
Specifically, you are:An engineer first - you design and ship complete production systems from scratch, across the full stack: data integration, agent orchestration, prompt and context engineering, evaluation, deployment, and monitoringBusiness-fluent - you can walk into a sales standup, a field operations review, or a GM strategy session and come out with a clear list of the highest-ROI AI opportunities in the room, without anyone handing you a briefSelf-directed - you do not need a spec, a PM, or a fully defined sprint to get started; you get handed a business outcome and you figure out how to build the system that delivers itAdaptive - every business unit runs a different stack; you learn the tools, find the integration points, and build on what exists - whether that is Zoho CRM, Microsoft Outlook, Slack, Meta Ads Manager, or something you have never touched beforeOutcome-obsessed - you define what success looks like before you build, and you measure it
in production; ROI on your agentic systems is your scorecard, not technical throughputAn effective communicator across roles - you can explain what you are building to a GM, a frontline sales rep, and a backend engineer using three completely different vocabularies, all in the same weekProduction-minded - your systems run in production, monitored, evaluated, and maintained; prototypes and demos are just the first five minutes of the workAnd you bring: Deep, hands-on experience building agentic AI systems - multi-step reasoning, tool use and function calling, orchestration, multi-agent workflows, retrieval, memory, and evaluationA track record of shipping AI systems against real business metrics, not just technical benchmarksIntegration experience across business application APIs - CRM platforms, email and marketing tools, calendar systems, communication tools, advertising platforms, or similarWhat You'll Do: Embed with an assigned business unit and participate in
their operational cadences - standups, pipeline reviews, field debriefs, ops meetings - as an active contributor, not an observerIdentify, scope, and prioritize agentic AI opportunities proactively and independently - without waiting for a product manager to hand you a projectBuild and ship complete production systems end to end: from business problem definition through integration, orchestration, prompt engineering, evaluation design, deployment, and ongoing monitoringOwn the ROI of every agentic workflow you deploy - define what success looks like, instrument it in production, and report results clearly to the business unit and the AI Engineering LeadWork directly with GMs, functional leaders, frontline teams, and operators - developing enough context about their actual work to identify AI leverage points they have not yet articulatedIntegrate across the full technology stack of the assigned business unit - CRM, email and marketing platforms, scheduling
systems, ERP, field management tools, advertising APIs, and others as requiredManage your deployed systems in production - monitor behavior, run regression evals, identify drift, and improve continuously as the business evolvesExtract reusable integration patterns, orchestration templates, and evaluation frameworks from your unit-specific work and contribute them back to the shared AI engineering libraryStay current on the rapidly evolving agentic AI landscape - new orchestration approaches, model capabilities, and framework patterns - and bring proven advances into production when they raise the ceiling on what is achievableRequirements: What We're Looking For: Demonstrated experience designing and shipping production agentic AI systems - not prototypes, not fine-tuning exercises, not proof-of-concept demosStrong software engineering fundamentals - this role builds real systems, not wrappers; you write code, design integrations, and own what you deployHands-on depth
across the agentic AI stack: orchestration frameworks, tool use and function calling, retrieval-augmented generation, multi-agent design, context engineering, and evaluationComfort operating with high autonomy and ambiguity - staff-level judgment about what to build and how, given a business problem and a desired outcomeDemonstrated ability to work directly alongside non-technical stakeholders - translating business problems into technical architectures independently, without a product layer in betweenIntegration experience with business application APIs: CRM, email and marketing platforms, calendar systems, communication tools, advertising APIs, or similarExperience designing and running evaluation suites for agentic systems - you do not ship agents without a baseline and a monitoring strategyStrong communication - you document what you build, explain how it works, and surface what is not workingStrongly Preferred: Prior experience as a forward-deployed
engineer, embedded technical consultant, or solutions engineer in an AI or enterprise software contextExperience building multi-agent systems - orchestrator/worker patterns, agent-to-agent coordination, shared state managementFamiliarity with MCP (Model Context Protocol) or similar agent-to-tool integration standardsBackground building agentic systems for sales, customer operations, field services, or business development workflowsExperience operating within small, high-autonomy teams where you owned the engineering direction on a project end to endTrack record of shipping AI systems that changed operational or financial metrics - with the numbers to show for itBenefits: Luxer Has Got You Covered!