Principal Architect

RESPONSIBILITIES

Applies extensive knowledge of theories, practices and design matters.

Works on issues that impact program success or addresses future concepts and products. Implementation of solutions requires a longer-term view which impacts strategic goals and objectives spanning several functions.

Exercise a wide latitude in determining objectives and approaches to critical assignments.

Knowledge with broadcast production or video content management systems

Knowledge of media management strategies and distribution workflows

Lead and contributes to development of company objectives across and principles to achieve goals

Deep understanding of AWS/Azure services and products

Provide feasibility reviews for potential new projects, including development effort estimates

Strong understanding of the C4 model and traditional design artifacts

Work with Engineering and Quality Assurance to identify and address reported issues quickly and effectively

Build and maintain scalable backend microservices using Python and FastAPI, deployed as varying serverless infrastructure.

Develop tools, constraints (guardrails), and deterministic functions that our AI agents use to edit visual assets. Integrate models on owned infrastructure for inference and integrate third-party AI endpoints.

Implement complex distributed workflows for high-volume job orchestration and dispatching (e.g. EventBridge, queues, DynamoDB streams).

Terraform contributions to provision and mange cloud resources safely and effectively across multiple environments.

Contribute to our modern backend orchestration or modern web frontends.

Write robust unit and end-to-end tests to ensure the stability of both standard APIs and AI agent outputs, ensuring smooth deployments.

REQUIRED QUALIFICATIONS

7+ years of professional software engineering experience with strong SDLC and version control expertise

Advanced Python proficiency with hands-on AWS/Azure/GCP deployment and operations experience

Proven experience integrating LLMs into production applications, including inferencing endpoints, context management, and AI output parsing

Practical Terraform or equivalent Infrastructure-as-Code experience for cloud resource management

Deep expertise in digital and broadcast production operations and workflows

Demonstrated mastery of C4 model and traditional design artifacts

Strong commitment to clean, maintainable, well-tested code with agile and code-review discipline

Current knowledge of AI industry trends and best practices

BS in Computer Science, Electrical Engineering, or equivalent professional experience

PREFERRED QUALIFICATIONs

5+ years of AWS cloud experience

1+ years of Azure cloud experience

Experience with Java, Golang, or JavaScript in addition to Python

Continuous integration and deployment pipeline experience

All your information will be kept confidential according to EEO guidelines.

EEOC and Veteran Documentation

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Administrative EEO Records are kept in a Confidential File and are not part of your Application for Employment or Personnel file.

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