Staff Software Engineer – Engineering Data Platform

Mojo Vision; Cupertino (CA); On-site; USD 141,000 - 211,000; Full time

Job summary

Mojo Vision in Cupertino, CA seeks a Senior Platform Architect to define the architecture for Mojo’s engineering knowledge and data platform. You will design scalable data models, ingestion pipelines, and services that unify experiments, simulations, and manufacturing data.

You will drive adoption by partnering with engineers, define standards, and shape how AI-assisted design systems leverage engineering data across Mojo Studio and related tooling.

Qualifications

• BS, MS, or PhD in Electrical Engineering, Optical Engineering, Physics, Mechanical Engineering, Computer Engineering, or a related field.
• 8+ years building production-grade software platforms, backend systems, or data-intensive applications.
• Demonstrated success leading architecture and implementation of large-scale technical systems.
• Strong experience designing and operating cloud-native systems on AWS.
• Deep understanding of APIs, relational data models, object storage, queues, event-driven systems, and data-processing pipelines.
• Experience designing data-modeling skills, including metadata, identifiers, schema evolution, lineage, and complex relationships.
• Expertise with infrastructure-as-code, containers, CI/CD, monitoring, and production operations.
• Strong understanding of data quality, validation, observability, security, reproducibility, and failure handling.
• Ability to work effectively in ambiguous environments and translate complex engineering needs into practical software.

Responsibilities

• Define and own the technical architecture for Mojo’s engineering knowledge and data platform.
• Design scalable systems that unify experimental, simulation, manufacturing, and analysis data.
• Create data models that represent complex engineering workflows, relationships, provenance, and metadata.
• Develop services, APIs, ingestion pipelines, and core platform capabilities.
• Integrate data from laboratory equipment, simulations, manufacturing systems, and engineering tools.
• Establish data quality, lineage, observability, governance, and security.
• Partner with engineers and domain experts across disciplines to drive adoption and standardization.
• Build systems that reduce effort and improve efficiency for engineers.
• Help define how AI systems interact with engineering knowledge and design data.

Skills

Cloud-native AWS

API design

Data pipelines

Infrastructure as code

Containers

CI/CD

Observability

Security

Distributed systems

Data modeling

Education

PhD in EE / Optical / Physics / CE

Masters or PhD in CS preferred

Tools

AWS services (S3, RDS, ECS/EKS, Lambda, SQS, IAM)

Workflow orchestration

Knowledge graphs / provenance

Job description

Mojo Vision is pioneering a highly flexible, wafers-in, wafers-out micro-LED platform to unlock AI applications in multiple market segments. Built over nine years by our skilled engineers, our system-level approach combines advanced 300mm silicon architecture with GaN-on Silicon emitters, proprietary quantum dots, photodetectors, micro-lens arrays, and packaging to solve conventional trade-offs in size, brightness, bandwidth density, and power. Our we are building breakthrough micro-display and next-generation optical interconnect products.

At Mojo, our team includes talented professionals with expertise in product design, user experience, applied physics, hardware, software, optics, photonics, electronics, chemistry, and vision science.

We are a startup founded by technology experts with decades of experience developing pioneering products and platforms backed by some of the world's leading technology investors in Cupertino, CA.

Roles and Responsibilities:

Engineering organizations generate enormous amounts of knowledge through simulations, experiments, manufacturing processes, analysis pipelines, and design decisions. Most of that knowledge remains fragmented across documents, scripts, spreadsheets, databases, and individual expertise. We're changing that.

Architect the Platform:

• Define and own the technical architecture for Mojo’s engineering knowledge and data platform.
• Design scalable systems that unify experimental, simulation, manufacturing, and analysis data.
• Create data models that represent complex engineering workflows, relationships, provenance, and metadata.

Build the Foundation:

• Develop services, APIs, ingestion pipelines, and core platform capabilities.
• Integrate data from laboratory equipment, simulations, manufacturing systems, and engineering tools.
• Establish data quality, lineage, observability, governance, and security.

Drive Adoption:

• Partner closely with engineers and domain experts across multiple disciplines.
• Simplify workflows while standardizing how engineering information is captured and shared.
• Build systems that engineers genuinely want to use because they make work easier, faster, and more effective.

Shape the Future:

• Help define how AI systems interact with engineering knowledge and design data.
• Contribute to the evolution of Mojo Studio, our AI-assisted co-design simulation platform.
• Influence company-wide technology strategy through hands-on technical leadership.

Qualifications:

• BS, MS, or PhD in Electrical Engineering, Optical Engineering, Physics, Mechanical Engineering, Computer Engineering, or a related field.
• 8+ years building production-grade software platforms, backend systems, or data-intensive applications.
• Demonstrated success leading architecture and implementation of large-scale technical systems.
• Strong experience designing and operating cloud-native systems on AWS.
• Deep understanding of APIs, relational data models, object storage, queues, event-driven systems, and data-processing pipelines.
• Experience designing data-modeling skills, including metadata, identifiers, schema evolution, lineage, and complex relationships.
• Expertise with infrastructure-as-code, containers, CI/CD, monitoring, and production operations.
• Strong understanding of data quality, validation, observability, security, reproducibility, and failure handling.
• Ability to work effectively in ambiguous environments and translate complex engineering needs into practical software.

Preferred Skills:

• Masters or PhD in Computer Sciences preferred
• Scientific computing or engineering software
• Semiconductor, EDA, photonics, or advanced manufacturing systems
• AWS services such as S3, RDS, ECS/EKS, Lambda, SQS, and IAM
• Workflow orchestration and distributed processing
• Knowledge graphs, provenance, or lineage-based systems
• AI infrastructure, MLOps, or agent-facing data platforms
• Authentication, authorization, and data-governance systems

This is a rare opportunity to serve as the technical leader for a strategic platform initiative. You will define the architecture, establish engineering standards, and help create the data foundation that enables AI-assisted engineering and future intelligent design systems.

If you're excited by complex technical challenges, ambiguity, and the chance to build something foundational from the ground up, we'd love to talk with you.

Salary Range: $141,000-$161,000-$211,000