Staff Software Engineer - AI

Luxer One•Mcclellan, CA

1d•$145,000 - $180,000•Hybrid

About The Position

Luxer One is the leader in smart locker and package management solutions across multifamily, commercial, retail, and enterprise markets. We design, manufacture, and deploy intelligent locker systems that move packages, assets, and people more efficiently — serving millions of transactions per year across North America. As the Assa Abloy Secure Lockers Division, we combine the resources of a global leader with the speed and focus of a product-driven technology company. We are building the AI infrastructure that will define how this business operates over the next decade — not as an experiment, but as the production backbone of our sales, operations, customer success, and field teams. Most AI initiatives inside companies fail the same way: compelling demos, no production systems. The gap is not the AI. It is the last mile — getting powerful models into the actual workflows that run the business. That is what this role is built to solve. Luxer One is embedding Forward Deployed Agentic AI Engineers directly inside business units across the organization. These engineers do not sit in a central platform team waiting for tickets. They embed with GMs, sales leaders, operations teams, and customer success functions. 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. This is the fastest-growing engineering archetype in the industry. Palantir built a category-defining company around it. OpenAI, Anthropic, Google, AWS, and Microsoft are each building internal versions at scale. We are doing it from the inside, deploying this model across our own divisions. If you have ever looked at a broken sales workflow, a high-volume support queue, or a manual operations process and thought "I could build an AI system that eliminates this" — and then actually built it — read on.

Requirements

Demonstrated experience designing and shipping production agentic AI systems — not prototypes, not fine-tuning exercises, not proof-of-concept demos
Strong software engineering fundamentals — this role builds real systems, not wrappers; you write code, design integrations, and own what you deploy
Hands-on depth across the agentic AI stack: orchestration frameworks, tool use and function calling, retrieval-augmented generation, multi-agent design, context engineering, and evaluation
Comfort operating with high autonomy and ambiguity — staff-level judgment about what to build and how, given a business problem and a desired outcome
Demonstrated ability to work directly alongside non-technical stakeholders — translating business problems into technical architectures independently, without a product layer in between
Integration experience with business application APIs: CRM, email and marketing platforms, calendar systems, communication tools, advertising APIs, or similar
Experience designing and running evaluation suites for agentic systems — you do not ship agents without a baseline and a monitoring strategy
Strong communication — you document what you build, explain how it works, and surface what is not working

Nice To Haves

Prior experience as a forward-deployed engineer, embedded technical consultant, or solutions engineer in an AI or enterprise software context
Experience building multi-agent systems — orchestrator/worker patterns, agent-to-agent coordination, shared state management
Familiarity with MCP (Model Context Protocol) or similar agent-to-tool integration standards
Background building agentic systems for sales, customer operations, field services, or business development workflows
Experience operating within small, high-autonomy teams where you owned the engineering direction on a project end to end
Track record of shipping AI systems that changed operational or financial metrics — with the numbers to show for it

Responsibilities

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 observer
Identify, scope, and prioritize agentic AI opportunities proactively and independently — without waiting for a product manager to hand you a project
Build and ship complete production systems end to end: from business problem definition through integration, orchestration, prompt engineering, evaluation design, deployment, and ongoing monitoring
Own 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 Lead
Work 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 articulated
Integrate 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 required
Manage your deployed systems in production — monitor behavior, run regression evals, identify drift, and improve continuously as the business evolves
Extract reusable integration patterns, orchestration templates, and evaluation frameworks from your unit-specific work and contribute them back to the shared AI engineering library
Stay 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 achievable