Lead the design, development, and delivery of AI-driven capabilities across technology platforms
Scale Applied AI and generative AI initiatives while collaborating with product, data, and business teams
Coordinate with multiple teams to drive innovation, ensure delivery excellence, and align AI capabilities with business goals
Build and nurture a team of AI Engineers and improve the technical foundation for Applied AI engineering team going forward
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
Drive development of custom AI solutions using Retrieval-Augmented Generation (RAG) pipelines and model fine-tuning
Design and lead systems that extract value from large structured and unstructured datasets
Build Agentic AI systems that streamline & automate workflows using LLMs
Cultivate a culture of experimentation, engineering rigor, and inclusiveness
Oversee the full lifecycle of Agentic AI applications
Partner with Data Engineering and Data Science teams to design data pipelines and experimentation workflows
Drive AI-enabled data accessibility across the organization
Partner with Product and Business Analysts team to co-develop AI-enabled features
Work closely with Application Engineering teams to embed Agentic AI into production systems
Build and maintain scalable, cloud-based AI infrastructure

8 or more years of technology engineering work experience including 2+ years in Applied AI software integration experience
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.

Director of Engineering, Applied AI

Key skills