Director, AI Experience Engineering

Director, AI Experience Engineering
The Director, AI Experience Engineering is a technology leader responsible for driving the adoption of AI-powered applications, agentic solutions, and intelligent developer experiences across the enterprise. This leader combines strong technical expertise with engineering leadership to enable teams to build, deploy, and scale AI solutions securely and efficiently.
This role works closely with Platform Engineering, Governance, Data, and AI teams to drive adoption of AI-powered applications, agents, and AI developer experiences across the organization. The successful candidate will enable engineering teams through reusable platforms, frameworks, tools, and best practices that accelerate innovation, improve developer productivity, optimize AI consumption, and deliver business value at scale.

Key Responsibilities and Duties

• Define and execute enterprise AI experience strategy across AI-powered applications, intelligent assistants, conversational experiences, and workflow automation
• Establish reusable patterns and practices that enable teams to rapidly develop and scale AI solutions
• Lead development and adoption of enterprise agentic platforms and Agent Marketplace capabilities for discovering, sharing, and consuming AI agents, MCP servers, prompts, skills, and tools
• Drive standards for agent orchestration, Model Context Protocol (MCP) integrations, and reusable AI capabilities across the organization
• Design and evolve AI-enabled developer experiences, including self-service platforms, AI-powered coding assistants, developer portals, and reusable SDKs
• Drive adoption of enterprise AI platforms and model-serving capabilities supporting AI application development and deployment
• Establish engineering standards for model integration, inference optimization, observability, scalability, and cost-efficient AI consumption
• Influence technology strategy and investment decisions related to AI platforms, agent ecosystems, model providers, and developer tooling
• Lead engineering teams delivering enterprise AI capabilities and foster a culture of innovation and AI adoption
• Partner with business and technology leaders to improve AI value realization through governance, consumption optimization, and token economics
• Define, track, and report adoption metrics such as active users, API/agent consumption volume, developer onboarding time, and platform reuse rates
• Drive strategies to increase adoption of AI platforms and tools across engineering teams, including onboarding programs, internal evangelism, and removal of adoption barriers

Educational Requirements

• University (Degree) Preferred

Work Experience

• 8+ Years Required; 10+ Years Preferred

Physical Requirements

• Physical Requirements: Sedentary Work

Career Level
10IC

Required Qualifications

• 8+ years of professional experience in software engineering, platform engineering, or AI/ML engineering roles
• Experience leading the design, build, and production deployment of at least one AI-powered application at scale
• Experience integrating with at least one major LLM provider or platform in a production environment
• Experience architecting or operating cloud-native systems, including containerized deployments, APIs, and microservices, at enterprise scale
• Experience defining and reporting measurable outcomes/metrics from a technology or platform initiative

Preferred Qualifications

• Hands-on experience with LLM application frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
• Experience implementing RAG architectures and vector databases such as Pinecone, Weaviate, FAISS, or pgvector
• Familiarity with Model Context Protocol (MCP), tool-calling standards, and agent orchestration frameworks
• Experience integrating with major LLM/AI providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or Google Vertex AI
• Understanding of Agent Marketplace concepts, internal developer platforms, and AI enablement ecosystems
• Knowledge of AI-assisted software development tools such as GitHub Copilot, Cursor, or Kiro

Related SkillsBusiness Acumen, Data Preprocessing, Data Science, Innovation, Machine Learning, Market/Industry Dynamics, Predictive Modeling, Programming, Statistics

Anticipated Posting End Date:

2026-10-31Base Pay Range: $221,000/yr - $251,000/yr

Actual base salary may vary based upon, but not limited to, relevant experience, time in r…