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Software Engineer, Applications & Deployment Infrastructure

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: MRINetwork
Full Time position
Listed on 2026-06-29
Job specializations:
  • IT/Tech
    Robotics, AI Engineer (Applied/Software), Systems Engineer, SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 100000 - 140000 USD Yearly USD 100000.00 140000.00 YEAR
Job Description & How to Apply Below

Software Engineer, Applications & Deployment Infrastructure
Confidential Physical AI & Robotics Company | San Francisco Bay Area
Build the Infrastructure That Makes Intelligent Robots Work in the Real World

A rapidly growing robotics and AI company is seeking a Software Engineer, Applications & Deployment Infrastructure to help scale the deployment of next-generation intelligent robotic systems operating in real-world commercial environments.

This organization is developing advanced AI-powered robotic platforms capable of learning, adapting, and improving across diverse environments. As deployments expand, the challenge is no longer simply getting a robot to perform a task. The challenge is building the infrastructure, tooling, and operational systems that allow fleets of robots to be deployed, monitored, supported, and continuously improved at scale.

This role sits at the intersection of robotics, AI, cloud infrastructure, and field operations. You’ll help transform real-world deployment complexity into scalable engineering systems that improve reliability, accelerate deployments, and create continuous feedback loops between deployed systems and engineering teams.

If you’re energized by solving difficult systems problems and want to work on technology that exists far beyond the lab environment, this is an opportunity to have a direct impact on the future of Physical AI.

What You’ll Do
Build Deployment Infrastructure

Design and develop the platforms, tooling, and operational systems that support large-scale deployment of intelligent robotic systems.

Responsibilities include:

  • Fleet monitoring and observability platforms
  • Remote diagnostics and troubleshooting tools
  • Deployment and configuration management systems
  • Operational dashboards and support workflows
  • Data collection and failure analysis pipelines
Partner with Operations Teams

Work directly with deployment and field engineering teams to understand real-world operational challenges and improve scalability.

You will:

  • Convert manual processes into software-driven workflows
  • Standardize deployment practices across sites
  • Reduce operational friction and improve deployment velocity
  • Build systems that make each deployment easier than the last
Create Feedback Loops Between Field and Engineering

Develop infrastructure that captures valuable operational insights from deployed systems and makes them actionable.

This includes:

  • Collecting and organizing deployment data
  • Surfacing failure modes and edge cases
  • Enabling performance analysis across environments
  • Supporting continuous improvement of AI-driven systems
Build End-to-End Solutions

Contribute across multiple layers of the technology stack, including:

  • Backend services and APIs
  • Data infrastructure and analytics pipelines
  • Internal and customer-facing applications
  • Hardware and robotics integrations
  • Cloud and edge computing systems
Improve System Reliability

Help ensure intelligent robotic systems perform consistently in unpredictable real-world environments.

Areas of focus include:

  • Deployment robustness
  • System stability
  • Failure recovery
  • Observability and diagnostics
  • Operational scalability
What You’ll Bring
Required Qualifications
  • Bachelor’s degree or higher in Computer Science, Robotics, Computer Engineering, or a related technical discipline
  • 5+ years of professional software engineering experience
  • Strong computer science fundamentals and systems-thinking mindset
  • Expertise developing production software in Python
  • Experience designing and building scalable backend systems
  • Experience integrating cloud services with hardware, edge devices, or physical products
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes
  • Familiarity with cloud platforms including AWS, GCP, or Azure
  • Strong communication skills and ability to collaborate across multiple engineering disciplines
  • Comfort operating in fast-moving, high-growth environments with significant ownership and autonomy
Preferred Experience
  • Robotics, autonomous systems, or physical AI
  • Fleet operations and deployment infrastructure
  • Observability, monitoring, and diagnostics systems
  • Hardware-integrated software applications
  • Edge computing environments
  • ROS or robotics middleware
  • U…
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