Media & Entertainment AI Architect

Title: Media & Entertainment Technical Architect

Location: Los Angeles CA, New York

Type: FTE

• Architect and Design Solutions: Lead the design and implementation of robust, scalable, and secure cloud-native solutions for core Media & Entertainment clients, focusing on their end-to-end content lifecycle.
• Translate Conceptual to Technical Architecture: Convert business requirements and logical architecture into a concrete technology architecture, leveraging a defined set of cloud services and best practices.
• Domain-Specific Solutioning: Develop architecture for complex M&E workflows, including video engineering (transcoding, packaging, delivery), image processing, audio processing, text engineering, and the application of Video Language Models (VLMs) and other AI/ML for content analysis and enhancement.
• Performance Optimization / Engineering: Proven ability to tune performance of various AI driven cloud native solutions.
• Technology Stack Implementation: Define and govern the use of a technology stack that includes various cloud native and COTS products.
• Client Collaboration: Engage in detailed discovery sessions and ongoing collaboration with clients to understand their existing ecosystem, refine the indicative architecture, and ensure the proposed solution aligns with their strategic goals.
• Technical Leadership: Provide expert guidance to engineering teams on best practices for building and deploying M&E solutions, ensuring adherence to architectural principles of scalability, security, cost-effectiveness, and data governance.
• Technology Evaluation: Assess and recommend the right tools for the job, including the evaluation of third-party vendors and the potential reuse of existing client technologies to empower data-driven campaign management.
• Prototyping and Documentation: Create proof-of-concepts (POCs), prototypes, and detailed technical documentation, including architecture diagrams and design specifications, to guide development and implementation.

Required Skills Competencies

• AI/ML in Media (must-have): Demonstrable multiple project experience in building media solutions leveraging machine learning models for text, video, audio, images – particularly in areas like computer vision, image recognition, NLP for metadata extraction, and familiarity with Video Language Models (VLMs), LLMs, transformers, scikit-learn libraries.
• Cloud/Data Architecture (must-have): Proven experience designing and building solutions on any/all hyperscalers (AWS, GCP, Azure) with expertise in the specific services of the target architecture for: Data Ingestion, Data Lake/Lakehouse, Data Governance, Data Analytics (e.g. Snowflake, Databricks), Data Models, Data Intelligence, Serverless Architecture, Event-Driven, Microservices, Microbatch processing & Orchestrations, Integration patterns, media related components of the specific Hyperscalers. Experience on CDC, DDD, SaaS, PaaS, protocols – REST, gRPC, formats – JSON, Protobufs.
• Video and Audio Engineering (good-to-have): Proficiency with video/audio codecs (e.g., H.264, HEVC, AV1, AAC), streaming protocols (HLS, DASH), container formats (MP4, TS), libraries (ffmpeg) technologies. Experience with custom as well as COTS products will be an added advantage.
• Software Engineering Foundation (must-have): Proficiency in a high-level programming language (e.g., Python, NodeJS / Java) and a solid understanding of software development lifecycle (SDLC), CI/CD, and infrastructure as code (IaC).
• M&E Domain Expertise (nice-to-have): Deep, demonstrable experience in the Media & Entertainment technology landscape, with a strong understanding of content supply chains, digital asset management (DAM), and media workflows.
• Problem-Solving & Strategic Thinking: Ability to analyze complex technical challenges and business requirements, and design elegant, efficient, and forward-looking solutions.
• Communication & Stakeholder Management: Exceptional ability to communicate complex technical concepts to both technical and non-technical audiences, and to build consensus and drive architectural decisions with clients and internal teams.