Software Engineer for Robotics Operations (Elixir & GCP)

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta, and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning, and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

JOB OVERVIEW

Build practical software that makes Robotics Operations more effective. We are looking for a proactive engineer with a product and entrepreneurial mindset: someone who discovers opportunities, anticipates pain points, and turns them into useful, reliable software. You will deliver improvements quickly and own the tools we rely on, including applications originally built with AI-assisted coding.

You will be an engineer embedded with Operations, taking initiative to understand how teams work and where software can make the biggest difference. You will observe workflows, ask questions, and use feedback and data to uncover unmet needs, including problems users have learned to work around. You will help shape what gets built, rather than wait for a fully defined task list. Think like a product owner and execute as an engineer. Connect everyday friction to the bigger picture: delivery quality, operator effectiveness, and the ability to scale. Choose focused improvements that create meaningful value, test assumptions early, and adapt as you learn.

We value initiative, product judgment, and demonstrated impact over the length of an engineering résumé alone. Some solutions will start as lightweight prototypes or AI-generated applications. Your job is to bring the engineering judgment needed to make them dependable: understand the code, fix defects, improve the design where needed, add appropriate tests and monitoring, and support the application as operational needs and underlying systems change. You will personally build, ship, and maintain production code.

AI-assisted development is encouraged, but you must be able to evaluate the output, debug it independently, and take responsibility for its behavior in production. You will work across several programming languages. Our primary system is Elixir-heavy. Previous Elixir experience is not required, but you should be ready to learn quickly and become productive developing and maintaining Elixir applications. You will also work with applications and services on Google Cloud Platform (GCP).

You will work cross-functionally with Operations, Product Engineering, and other technical teams to make sure local improvements work with the wider system. Build shared understanding, surface dependencies early, and drive decisions through completion. You will know when a small Operations tool is the right answer, when an existing solution can be reused, and when a problem requires a coordinated change to shared services or core product functionality.

JOB DUTIES

• Discover needs before they become urgent. Proactively explore workflows with Operations, identify recurring friction and emerging failure points, and propose improvements before teams need to escalate a problem.
• Prioritize and deliver quick wins. Connect opportunities to operational goals, assess user impact, effort, and risk, and choose the smallest useful solution. Make clear recommendations about what to build, improve, reuse, or leave alone.
• Build iteratively with users. Deliver small, useful changes, gather feedback early, and refine solutions based on how people use them. Keep the scope focused while ensuring the result is safe and fit for its intended use.
• Own Operations applications. Maintain and improve internal tools, dashboards, automations, and integrations, including applications initially created through AI-assisted coding. Diagnose issues, resolve bugs, and keep tools working as dependencies and requirements evolve.
• Develop across our stack. Contribute in several languages, ramp up quickly on our Elixir-heavy core system, and build, deploy, troubleshoot, and support applications on Google Cloud Platform.
• Bring engineering discipline to AI-built software. Review generated code, understand its dependencies and data access, address security and reliability gaps, and add tests, documentation, monitoring, and maintainable structure appropriate to the application's risk.
• Drive cross-functional execution. Align Operations and Engineering on needs, owners, dependencies, and tradeoffs. Anticipate the effects of API, schema, authentication, and platform changes on Operations tools. Bring recommendations to the teams that own shared systems, resolve blockers, and follow through on commitments rather than building fragile workarounds.
• Champion practical AI adoption. Help Operations identify useful AI-assisted workflows, evaluate tools, and develop safe, repeatable practices. Help colleagues understand where AI saves time and where human review and engineering ownership are essential.
• Stay accountable after launch. Support the software you ship, investigate failures, and verify that improvements reduce operational friction or improve delivery quality. Favor durable fixes over recurring manual intervention.

EXPERIENCE, QUALIFICATIONS, & SKILLS

Required Experience, Qualifications, and Skills

• 5+ years of professional experience, with substantial software engineering experience and ownership of shipped software. We prioritize what you have identified, built, and improved over tenure alone.

• Strong production coding capability. You can independently design, implement, test, debug, deploy, and maintain applications. You can understand and improve an unfamiliar codebase, including code generated with AI assistance.

• Google Cloud Platform experience. You have built, deployed, or supported applications and services on GCP and can troubleshoot their behavior in a cloud environment.

• Ability to learn and contribute across languages. You can become productive quickly in an unfamiliar stack. Prior Elixir experience is not required; learning it quickly and contributing to our Elixir-heavy system is an expectation of the role.

• Experience building useful applications, internal tools, automations, or integrations for business or operational users.

• A proactive, self-starting approach. You can find a worthwhile problem, investigate it independently, propose a path forward, and take ownership without waiting for detailed instructions.

• Product and entrepreneurial judgment. You understand user needs, challenge assumptions, balance speed with quality, and focus effort on solutions people will use. You can create clarity and momentum when the problem or solution is not yet well defined.

• Big-picture thinking. You connect a local workflow improvement to broader operational goals, recognize upstream and downstream effects, and avoid optimizing one tool at the expense of the wider system.

• Sound judgment about testing, code review, access controls, sensitive data, dependency management, observability, and production support.

• A practical, iterative approach: you can deliver a small improvement quickly without losing sight of reliability, maintainability, or user needs.

• Ability to work directly with non-engineering users, clarify ambiguous requests, explain tradeoffs, and turn feedback into working improvements.

• Cross-functional leadership through influence: you can bring operational and engineering perspectives together, explain tradeoffs, secure alignment, and keep work moving through release and adoption.

• Interest in AI-assisted development and workflow automation, paired with the ability to validate results and recognize limitations.

• Previous experience managing an operations team is not required. This role is centered on building and supporting software for Operations, rather than managing a program or coordinating other engineers' delivery.

Preferred Experience, Qualifications, and Skills

• Experience with operator-facing applications, workflow automation, dashboards, or fleet and robotics tools.

• Full-stack development experience, including user interfaces, services, APIs, and data integrations.

• Previous experience developing applications in Elixir.

• Experience taking a prototype or lightly engineered application into dependable operational use.

• Effective use of AI coding assistants, with examples of reviewing, correcting, testing, and maintaining their output.

• Experience owning a product or internal tool from discovery through adoption and iteration, or building useful solutions in an entrepreneurial environment.

• Experience helping non-technical teams adopt AI tools responsibly.

• Robotics, autonomous vehicles, logistics, delivery, or other technology-enabled field operations experience.

What success looks like

• Operations receives useful improvements in short iterations, with feedback shaping subsequent work.
• Important needs and risks are surfaced early, with solutions initiated before they become urgent requests or recurring incidents.
• Tools are adopted and deliver measurable value, with low-value ideas changed or stopped based on evidence.
• Cross-functional partners have clear ownership and fewer surprises as tools and underlying systems evolve.
• High-value internal applications have clear technical ownership and dependable support.
• AI-built tools become easier to understand, test, change, and maintain.
• Changes to shared engineering systems cause fewer avoidable disruptions to Operations tools.
• Teams spend less time on repetitive work and recurring software issues.
• AI adoption produces practical benefits without compromising data handling, reliability, or engineering standards.