Principal Software Architect | Luma

Dotmatics•Boston, MA

3d•$173,400 - $234,600•Remote

About The Position

Dotmatics is seeking a Principal Engineering Architect to shape the architecture of Luma, a next-generation, multi-tenant, AI-powered data management and workflow automation platform for multimodal scientific discovery. The role designs and refines AWS systems for deploying Luma to customers and provides influential technical leadership and advice to Engineering and Product teams. The architect supports the platform’s development and delivery, including connections among scientific instruments, scientific data, platform services, and the AI agent experience. The role also addresses customer-cloud deployments, including multi-tenant and regulated-environment needs, and works with customer cloud teams. This is a hands-on leadership role involving architectural direction, technical prototyping, implementation guidance, technology choices, and strategic initiatives. The architect will help establish principles, frameworks, best practices, standards, and secure connections for AI agents and extension points such as MCP. They will facilitate architecture reviews and documentation, mentor engineers, improve developer experience and software lifecycle practices, and advise on Luma product strategy. Dotmatics describes its environment as collaborative, global, and remote-friendly. The stated base pay range is $173,400–$234,600 USD. Compensation is based on job-related skills, experience, qualifications, and location; some positions may also be eligible for variable pay.

Requirements

BSc in Computer Science, or equivalent, and 10+ years of experience.
Deep technical expertise in engineering architecture and engineering design.
Expert knowledge of building, releasing, and maintaining a complex scientific enterprise software platform.
Deep understanding of modern cloud software architecture, including multi-tenant platforms.
Systems design and development experience, with a solid understanding of application development best practices and core enterprise applications.
Deep knowledge of AWS services.
Knowledge of cloud-native infrastructure such as Kubernetes and Kafka.
Working technical knowledge of integration strategies, including web services and APIs.
Experience setting up agentic harnesses for code generation.
Ability to communicate influentially with core and cross-functional teams.
Experience with infrastructure-as-code solutions such as CloudFormation and Terraform.
Knowledge of software containerization concepts such as Docker and Podman.
Experience with CI/CD tools such as Jenkins, TeamCity, and CodePipeline.
Knowledge of networking concepts in cloud environments.
Knowledge of software development lifecycle processes and version control.
Knowledge of modern back-end JavaScript and Node.js, and Python.
Business requirements gathering and analysis, strategic planning, and project planning and management skills.
Knowledge of engineering evaluation principles and practice.

Nice To Haves

Instrument integration and scientific data ingestion experience, such as SiLA or OPC-UA.
Experience with Apache Spark, Databricks, or comparable data platforms.
Experience securing AI agent integrations, including permissions, sandboxing, and prompt injection defense.
Experience using research informatics software and tools.
Knowledge of Scala.

Responsibilities

Support and drive Luma’s end-to-end architecture, from instrument connectivity and data ingestion through platform services and the AI agent experience.
Influence technology choices for the platform.
Design enterprise-scalable and maintainable solutions, with data isolation and auditability for regulated scientific customers.
Collaborate on architectural principles, frameworks, best practices, and standards, including secure connections between the AI agent, extension points such as MCP, and platform services.
Drive strategic technology initiatives with Product Managers, other Architects, and Engineers.
Contribute hands-on to Luma development and delivery, including prototyping and guiding component implementation.
Improve developer experience and the software lifecycle by proposing tools and pipelines that improve software development quality.
Advise the product team on requirements for deploying Luma into customer clouds, including multi-tenant and regulated-environment needs.
Work with customer cloud teams.
Facilitate architecture processes, including reviews and documentation.
Mentor software engineers on the team.
Shape projects in a timely manner to established architecture patterns.
Improve communication, collaboration, and alignment among internal and external teams through a consultative approach.
Analyze and provide feedback on Luma product strategy.