> Markdown version of [/jobs/ext/3761552-ai-prompt-engineer-media-industry-remote](https://www.wearedevelopers.com/jobs/ext/3761552-ai-prompt-engineer-media-industry-remote). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Prompt Engineer (Media Industry) Remote - **Company:** Techaffinity Consulting - **Location:** United States (Remote available) - **Contract:** Contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, JSON, Python (Programming Language), Delivery Pipeline, Large Language Models, Prompt Engineering, AWS Lambda, Amazon Bedrock, Claude, Video Analysis, Model Inference, Data Pipelines, Automation Anywhere - **Published:** October 15, 2026 - **Apply:** https://www.dice.com/job-detail/bd25eabf-c005-4032-b3ba-1ac5960032d9 ## About the Role Strong experience in: * Prompt engineering for foundation models such as Claude, Nova, etc. * Multimodal AI systems covering vision and NLP * LLM inference and optimisation * Structured outputs, including JSON generation and validation * Strong Python programming and data pipeline development * AWS cloud stack, particularly: * Bedrock * Lambda * S3 * Analytics/data pipelines Video analytics or media AI workflows Real-time or near-real-time AI systems ## Description * Design and optimise prompt engineering strategies for foundation models * Build pipelines for multimodal inference across: * Video * Transcript * Audio Detect and classify custom moments and contextual events Develop reusable frameworks for: * Moment detection templates * Structured metadata generation * Prompt optimisation Fine-tune prompts and configurations to improve: * Accuracy * Precision across different moment types Integrate GenAI outputs into: * Structured JSON metadata * Downstream systems * Data processing pipelines Work with AWS services including: * Amazon Bedrock * AWS Lambda * Amazon S3 * Amazon Kinesis Collaborate with the QA team for output validation and optimisation Support production rollout and continuous improvement