Director of Engineering, Applied AI

About the role

A+E Global Media is seeking a strategic and hands-on Director of Engineering, Applied AI to lead the design, development, and delivery of AI-driven capabilities across our technology platforms. Reporting directly to the VP, Corporate Application Engineering & Enterprise Data, you will play a critical role in scaling our Applied AI and generative AI initiatives while collaborating with product, data, and business teams to bring next-generation media experiences to life.

Responsibilities

• Drive the technical roadmap for Applied AI across key enterprise applications and business workflows.
• Evaluate and implement cutting-edge AI techniques, frameworks, and best practices including LLMs to ensure the team remains at the forefront of innovation and leverages the best available tools for media and entertainment use cases.
• Design and lead systems that extract value from large structured and unstructured datasets — including PDFs in S3, SharePoint documents and emails using LLMs, RAG, RLHF, and enterprise-scale modern AI techniques.
• Build Agentic AI systems that streamline & automate workflows using LLMs.
• Cultivate a culture of experimentation, engineering rigor, and inclusiveness where bold ideas are tested quickly and learned from openly.
• Oversee the full lifecycle of Agentic AI applications, from prototyping and data exploration through model integration, orchestration, deployment, monitoring, and retraining.
• Partner with Data Engineering and Data Science teams to design robust, reusable data pipelines and experimentation workflows that accelerate Applied AI initiatives.
• Drive AI-enabled data accessibility across the organization, delivering solutions and tooling that empower stakeholders at all levels, from analysts to senior executives to extract actionable insights.
• Partner with Product and Business Analysts team to co-develop AI-enabled features and prioritize high-impact initiatives.
• Work closely with Application Engineering teams to embed Agentic AI into production systems, improve user experience, ensuring seamless integration, scalability, and long-term maintainability.
• Drive engineering excellence and delivery cadence across the AI stack — observability, latency, model monitoring, evaluation harnesses, rollback paths, and sprint-level prioritization across concurrent workstreams.
• Build and maintain scalable, cloud-based AI infrastructure that supports rapid experimentation, model serving, and cost-controlled inference at media-scale workloads.
• Champion responsible AI development aligned with privacy, IP, copyright, and ethical standards — particularly relevant for media content and audience data.

Requirements

• Required 8 or more years of technology engineering work experience including 2+ years in Applied AI software integration experience.
• Will have 3 or more years of team leadership experience.
• Experience with Python and/or Typescript/Javascript.
• Well-versed in SQL.
• Experience working with LLM provider APIs (e.g., OpenAI, Anthropic, Google Gemini) and frameworks (e.g., LangChain, LlamaIndex, AutoGen, AI SDK) to build agentic or multi-agent AI workflows.
• Experience in building and deploying AI-powered applications at scale, with a strong focus on applying large language models (LLMs) to real-world products and workflows.
• Experience working with Agentic AI, Embeddings, RAG, RLHF and other AI techniques at enterprise scale.
• Experience designing or applying evals on systems built on top of LLMs, including prompt testing, grounding, hallucination detection, and performance benchmarking.
• Excellent communication skills and experience working on cross-functional initiatives.

Qualifications

• Preferred Experience with agentic AI harnesses and orchestration frameworks (e.g., LangGraph, Semantic Kernel) for building, managing, and deploying multi-agent systems is a plus.
• Experience working with big data and data warehouse projects is a plus.
• Familiarity with vector databases and RAG pipelines (e.g., Pinecone, Weaviate, Milvus, ChromaDB, pgvector) for LLM-powered applications is a plus.
• Experience building full-stack AI-powered applications using modern web frameworks (e.g., Next.js, React) to deliver user-facing AI products and internal tooling is a plus.
• Hands-on experience with ML/deep learning libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers, Scikit-learn) and deploying models to production is a plus.
• Experience with MLOps tooling (e.g., MLflow, Weights & Biases, Kubeflow) and cloud ML platforms (e.g., AWS SageMaker, Google Vertex AI, Azure ML) is a plus.
• Familiarity with data engineering tools and platforms (e.g., Databricks, Snowflake, Apache Spark, dbt, Kafka) is a plus.
• Familiarity with data privacy, copyright, and ethical issues in Applied AI applications is helpful but not needed.
• Experience in the media, entertainment, ad-tech, mar-tech or publishing industry is a plus.

Skills

• Strong technical background in applied AI, machine learning, and data science.
• Experience with large language models (LLMs) and their application to media and entertainment use cases.
• Expertise in building and deploying AI-powered applications at scale.
• Experience with Agentic AI, Embeddings, RAG, RLHF and other AI techniques at enterprise scale.
• Ability to design and apply evaluations on systems built on top of LLMs.
• Strong communication and collaboration skills.
• Experience with modern web frameworks and ML/deep learning libraries.
• Familiarity with data privacy, copyright, and ethical issues in Applied AI applications.

Benefits

The annual/hourly pay range displayed serves as a good faith estimate of the minimum and maximum base pay range for this role. Compensation for the role will be based on a number of different factors such as a candidate's qualifications, skills, competencies, location, and experience. A+E offers a competitive total compensation package, which includes healthcare coverage, 401k matching, and a range of other benefits.

Pay

Annual Pay Range: $188,034 - $220,000

Schedule

N/A