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Staff Software Engineer AI

Luxer One


Job Location:

Sacramento, CA - USA

Monthly Salary: USD 145000 - 180000
Experience Required: 5-8years
Posted: 2 October 2026 (17 hours ago)
Application Deadline: 30 December 2026
Vacancies: 1 Vacancy

Job Summary

About Luxer One

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.

Why This Role Exists

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.

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 monitoring

  • Business-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 brief

  • Self-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 it

  • Adaptive 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 before

  • Outcome-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 throughput

  • An 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 week

  • Production-minded your systems run in production monitored evaluated and maintained; prototypes and demos are just the first five minutes of the work

And 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 evaluation

  • A track record of shipping AI systems against real business metrics not just technical benchmarks

  • Integration experience across business application APIs CRM platforms email and marketing tools calendar systems communication tools advertising platforms or similar

What Youll 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 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


Requirements
What Were Looking For
  • 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

Strongly Preferred
  • 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


Benefits
Location & Work Model
  • Sacramento CA. On-site or hybrid
Benefits
Luxer Has Got You Covered!
  • You will have a 401k with up to 4.5% matching untracked vacation and a hybrid work schedule.
  • We promote education through tuition reimbursement.
  • You will also have medical dental vision and life insurance programs as well as employee assistance programs.
  • Youll have opportunities to advance.
  • Were fans of helping our employees learn different aspects of the business be challenged with new tasks be mentored and grow.
  • We promoted 42% of our employees last year!
Luxer One is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin age disability veteran status or any other legally protected status.

Compensation

The pay range for this role is $00 per year depending on experience skills and location. This range reflects what we believe in good faith wed pay for this position at the time of posting and final offers may vary based on qualifications and business needs.


Required Skills:

About Luxer One 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. Why This Role Exists 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. 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 monitoring Business-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 brief Self-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 it Adaptive 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 before Outcome-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 throughput An 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 week Production-minded your systems run in production monitored evaluated and maintained; prototypes and demos are just the first five minutes of the work And 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 evaluation A track record of shipping AI systems against real business metrics not just technical benchmarks Integration experience across business application APIs CRM platforms email and marketing tools calendar systems communication tools advertising platforms or similar What Youll 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 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 th


Required Education:

What Were Looking ForDemonstrated 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 e