Staff AI Engineer - Content Velocity
One year contract (most likely will extend)
Remote (within United States)
JOB DESCRIPTION:
Staff AI Engineer
For the engineering profiles, client wants candidates who are very strong in at least one cloud environment.
The specific cloud is less important than having strong depth, although his preference is:
AWS
Azure
Google Cloud Platform
Beyond cloud experience, the focus is increasingly on engineers who have experience building event-driven applications.
OVERALL SUMMARY
As part of the Operations & Technology Solutions Architecture team, Principal Architects are responsible for the architecture and maintenance of systems to support on-air reliability of numerous workflows for NBCUniversal’s broadcast and streaming channels. This includes internal business applications, new technology initiatives, and consumer-facing systems. The successful candidate will work closely with clients (users) to complete the analysis and design of systems and follow the implementation to completion. Principal Architects are expected to develop highly available, fault tolerant architectures following industry standards and best practices. They are expected to lead other architects and develop standards and best practices across the architecture landscape.
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/REQUIREMENTS
7+ years of professional software engineering experience with a strong grasp of the Software Development Life Cycle and version control.
Strong proficiency in modern Python. Hands-on experience deploying and operating services in AWS, Azure, and/or Google Cloud Platform.
Practical experience integrating LLMs into software applications. You must understand how to interact with inferencing endpoints, manage context windows, and parse AI-generated content.
Applied experience with Terraform or similar IAC tools to manage cloud resources.
A strong commitment to writing clean, maintainable, and well-tested code. Experience working in an agile environment with rigorous code-review standards.
Expert experience, understanding and knowledge of digital and broadcast production operations and workflows
Strong knowledge of AI industry trends and best practices
Strong experience with the C4 model and other traditional design artifacts
Experience working in an Agile environment
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