This team does not currently have dedicated AI Engineers, so this person will come in as one of the highest-level individual contributors on the AI side. The role is highly hands-on, but also requires leadership and cross-functional influence.
You'll partner closely with leadership and business teams to design and build scalable AI capabilities across the organization — helping connect systems, workflows, and teams into practical AI-driven solutions.
This is not a pure research role. They need someone who can actually build, operationalize, and scale AI products in production environments.
What They're Looking For
Strong hands-on engineering background with deep AI experience
Someone who has successfully implemented AI solutions in enterprise environments
Experience building and operationalizing AI agents, LLM workflows, and intelligent systems
Comfortable working closely with AI architects while owning execution and delivery
Able to work independently without heavy direction
Strong understanding of governance, controls, and responsible AI practices
Focused on making AI productive and usable within the business
Must-Have Experience
10 years of software engineering experience
3–5 years focused on AI/ML, intelligent systems, or data-intensive applications
2–3 years delivering AI/ML solutions in AWS environments
Strong Python development experience
Experience with AWS AI services including Bedrock, SageMaker, and serverless architectures
Experience with enterprise LLM systems, including:
RAG architectures
Vector databases/search
Prompt engineering
LLM evaluation and integrations
Experience building and deploying AI agents / agentic workflows
Experience integrating with enterprise platforms like Workday and ServiceNow
Understanding of governance, observability, metadata, lineage, and access controls
Experience working with unstructured data and document intelligence solutions