Associate Director, AI Foundations Engineering (3 Openings)

#LI-Remote

The Associate Director, AI Foundations Engineering will lead the engineering strategy, design, development, deployment, and ongoing optimization of our agentic AI platform and solutions. This role is responsible for building scalable, secure, and reliable AI-driven systems that transform existing products, processes, and workflows into intelligent, agentic AI experiences. As a key technical leader, the Associate Director will partner closely with product, data, architecture, security, and business teams to define platform capabilities, drive implementation excellence, and operationalize continuous improvement across the AI lifecycle. The ideal candidate brings deep expertise in AI engineering, platform architecture, and production operations, along with a strong track record of translating emerging AI capabilities into practical, high-impact business solutions.

This position can be based remotely anywhere in the U.S. (there may be some

restrictions based on legal entity). Please note that this role would not provide

relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the Hiring Manager.

There are 3 positions available.

Key Responsibilities

Lead the architecture, design, and engineering delivery of the organization's agentic AI platform and related solutions.

Drive the transformation of existing products, processes, and workflows into scalable agentic AI-enabled capabilities.

Oversee end-to-end AI engineering operations, including development, deployment, monitoring, reliability, and continuous improvement.

Partner with cross-functional stakeholders to define technical roadmaps, platform standards, and solution priorities aligned to business goals.

Establish engineering best practices for AI system performance, scalability, security, governance, and maintainability.

Guide the evaluation, integration, and optimization of AI models, orchestration frameworks, and supporting platform components.

Build, mentor, and lead high-performing engineering teams while fostering innovation, accountability, and technical excellence.

Identify opportunities to accelerate value delivery through reusable AI services, automation, and operational efficiencies.

Essential Requirements

Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience. An advanced degree is a plus but not required.

5+ years of professional software engineering experience, including at least 1–2 years building applications on large language models, with at least one agentic system deployed beyond a demo.

Hands-on experience building AI agents on AWS. This includes Amazon Bedrock (models, Agents, Knowledge Bases, Guardrails) and Bedrock AgentCore or comparable approaches for agent runtime, memory, tool access, and identity.

Proficiency with at least one agent framework, such as Strands Agents, LangGraph, LlamaIndex, CrewAI, or a custom orchestration layer. You should be able to explain when a simple workflow beats a multi-agent design.

Strong Python skills plus experience with AWS services commonly used in agent architectures: Lambda, Step Functions, ECS/EKS, API Gateway, DynamoDB, S3, and IAM.

Experience with retrieval-augmented generation (RAG), including chunking strategies, embeddings, vector stores (OpenSearch, pgvector, or similar), and improving retrieval quality.

Experience designing tool use and function calling so agents can connect to APIs, databases, and enterprise systems. Familiarity with Model Context Protocol (MCP) is preferred.