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Senior Staff Software Engineer - Cloud (Technical Lead Manager)

Brain Corp

LocationUnited States
Senioritylead
CompanyBrain Corp
Verification agingJul 26
Compensation

$214k-$267k

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Requirements and working style

Decision details from the source listing

Education

Master degree

Benefits stated
Paid time offRetirement plan

These fields are normalized from the employer's text. Confirm details on the employer site before applying.

WFH.team analysis

What this posting tells you

Role lane

Backend, Customer success, Data, Design and creative, DevOps, Education, Frontend, Healthcare admin, Legal, Medical billing, Mobile engineering, Operations, Product, Security, Software, Customer support

Where you can work

United States

Working hours

Timezone overlap is not stated.

Arrangement

lead · full_time

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  • Required timezone overlap is not stated
Market context

Backend hiring on WFH.team

6,091active related roles
3,247new in the latest period
286.2jobs per 100 candidates
$202kmedian of comparable listed ranges

This role's listed pay is above the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.

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Skills and signals
APICloudComputeDataDevopsDistributed SystemsGCPGoGoogle CloudInfrastructureKubernetesPlatformProductPythonSecuritySupportremote
Job description

Senior Staff Software Engineer - Cloud (Technical Lead Manager) at Brain Corp

Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock their abilities in orchestration with intelligent machines.

Position Overview

The Sr Staff Software Engineer - Cloud (Technical Lead Manager) is a key contributor within Brain Corp’s engineering organization leading the design and development of large-scale, high-availability systems powering Brain Corp’s cloud platform. This platform connects our global fleet of autonomous robots, manages data ingestion from the field, and supports advanced machine learning pipelines for perception, analytics, and operational insights. This dual role will serve as both a technical leader and people manager, guiding a team of cloud engineers while contributing hands-on to the architecture, design, and implementation of next-generation cloud services. The engineer will work closely with ML engineers, data scientists, and infrastructure teams to build scalable cloud-based machine learning systems that handle massive volumes of image data and deliver efficient inference at scale.

This role can be remote anywhere in the United States or hybrid at our office in San Diego. Relocation is available.

Essential Job Functions

Lead and manage a team of cloud software engineers, providing technical mentorship, career guidance, and performance management

Define and execute the cloud technical roadmap, ensuring alignment with Brain Corp’s business and product goals

Architect and implement high-availability, scalable, and secure systems on Google Cloud Platform (GCP) to support machine learning workloads and data ingestion at scale

Design, build, and operate ML pipelines that process hundreds of thousands of images daily, enabling rapid model iteration and deployment

Develop and optimize GPU resource management strategies, improving model serving throughput, latency, and cost efficiency

Build canary and staging environments to ensure safe, progressive deployments and system resilience

Collaborate cross-functionally with ML, DevOps, and robotics teams to define APIs, data models, and operational workflows for cloud–robot communication

Implement Infrastructure-as-Code (IaC) solutions using Pulumi, Terraform, or equivalent, ensuring repeatable and automated deployments

Establish and maintain cloud observability systems, ensuring reliability, performance, and security compliance

Drive technical excellence, setting coding standards, reviewing designs, and promoting best practices in distributed systems and cloud ML architectures

Stay current with advancements in GCP, ML infrastructure, and MLOps to continuously improve platform capabilities and team practices

Education and/or Work Experience Requirements

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field

10+ years of professional software engineering experience, including 3+ years in cloud architecture or large-scale distributed systems

3+ years of technical leadership or management experience, preferably in a Technical Lead Manager or team lead capacity

Proven experience designing and operating GCP-based ML systems at scale

Required Knowledge, Skills, Abilities and Other Characteristics

Expert-level knowledge of Google Cloud Platform (GCP) services such as GKE, Dataflow, BigQuery, Cloud Run, Pub/Sub, Vertex AI, and Cloud Storage

Strong proficiency in Go, Python, or TypeScript, with an emphasis on maintainable, production-quality code

Deep understanding of machine learning pipelines: data ingestion, preprocessing, training, deployment, and inference

Experience optimizing GPU workloads, autoscaling, and resource scheduling in cloud environments

Proven success in designing high-availability and fault-tolerant distributed systems

Hands-on experience with containerization and orchestration technologies (Docker, Kubernetes)

Familiarity with infrastructure-as-code tools (Pulumi, Terraform) and CI/CD systems (e.g., Jenkins, GitHub Actions)

Strong understanding of security, networking, and observability in cloud environments

Excellent problem-solving, communication, and leadership skills

Ability to balance hands-on technical work with people management responsibilities

Passion for robotics, automation, and enabling intelligence at scale

Things that Make a Difference

Experience in robotics data pipelines, fleet management, or IoT-scale data ingestion

Experience self-hosing ML inference

Hands-on experience with Vertex AI, Kubeflow, or TensorFlow Serving in production

Background in event-driven architectures and message streaming (e.g., Pub/Sub, Kafka)

Experience with SOC2/ISO27001-compliant systems and secure cloud practices

Familiarity with Agile methodologies and modern DevOps culture

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential functions may require maintaining the physical condition necessary for sitting, walking or standing for periods of time; operating a computer and keyboard; use of hands to finger and grasp; talk and hear at normal room levels; visual acuity to determine the accuracy, neatness, and thoroughness of the work assigned or to make general observations of facilities or structures; push or pull up to 20 pounds.

Work Environment

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

Salary Range

The anticipated salary range for candidates who will work in San Diego, California is $213,789 - $267,237. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi-state employer and this salary range may not reflect positions that work in other states.

In addition to base pay, our competitive total rewards package consists of:

A discretionary annual target bonus

Stock options

401(k) plan with match (no waiting period and immediate vesting)

Comprehensive suite of insurance benefits for employees (and their families) to include a variety of medical plan options (including an HSA with employer contribution), dental, vision, life and disability insurance, Employee Assistance Program (EAP), Legal/Identity support plans, pet insurance.

Access to Flexible Spending Accounts (Medical and Dependent Care)

Generous paid time off including flexible vacation, Paid Sick Leave, time off for volunteering in the community, 10 paid company holidays, and a winter company shutdown

Additional Perks include

Daily on-site lunch available in the San Diego office

On-campus gym including pool and tennis courts in the San Diego office

Opportunities to connect with colleagues including monthly game nights, hikes, wellness challenges, and community events

Internal continuous learning events

Opportunities to share your own interests and hobbies with the Company

Department: Software Engineering.

ATS provider: Greenhouse.

Salary: Salary Range: The anticipated salary range for candidates who will work in San Diego, California is $213,789 - $267,237. The final salary offered to a successful candidate will be dependent on several.

Company context

Working remotely at Brain Corp

Brain Corp is hiring for 1 active remote role, with remote-friendly openings, application links, and job details refreshed from the public remote job inventory.

Remote policy

Remote hiring signal is inferred from active confirmed-remote job listings.

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