Principal Architect

Job Description

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.

Qualifications

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

Additional Information

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

EEOC and Veteran Documentation

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