AI Cloud Data Architect | Onsite

Photon•Wilmington, DE

8h•$72,000 - $252,000•Onsite

About The Position

This is a hands-on player-coach role for an AI Cloud Data Architect. The individual will own the architecture and directly contribute to AI/ML builds, including prompt engineering, RAG patterns, and agent tuning. The role requires a senior individual who has shipped LLM systems on Bedrock, not a pure architecture profile. The architect will own the end-to-end target architecture for AI use cases on the AWS stack, with the data lake on Snowflake. Responsibilities include designing and building solutions on AWS Bedrock, implementing Bedrock Guardrails for content safety and accuracy, ensuring architectural alignment with existing MuleSoft investments, delivering agent layer code in the SLM-preferred framework, driving eval-harness design, collaborating on the modernization roadmap, owning architecture decision records, and coordinating the future integration roadmap with CRM, omnichannel exposure, and IVR.

Requirements

Must be staffed with a senior who has shipped LLM systems on Bedrock
100% AWS stack expertise
Snowflake data lake experience
Experience with prompt engineering, retrieval pipelines (RAG), and foundation model selection from Bedrock's catalog
Experience implementing Bedrock Guardrails for content safety, PII handling, and accuracy thresholds
Understanding of MuleSoft investment (full API lifecycle: design, testing, runtime, governance)
Familiarity with LangChain / LangGraph or AWS Strands
Experience driving eval-harness design for agent accuracy, hallucination rates, and regression
Experience owning architecture decision records (ADRs)
Experience coordinating integration roadmaps (CRM, omnichannel, IVR)

Nice To Haves

Experience in regulated lending environments
Experience with Sallie Mae's existing MuleSoft investment
Experience with the planned MuleSoft Agent Fabric control-plane
Experience with Salesforce CRM integration
Experience with web and mobile omnichannel exposure
Experience with IVR integration

Responsibilities

Owns architecture and directly contributes to AI/ML build (prompt engineering, RAG patterns, agent tuning)
Own the end-to-end target architecture for AI use cases on AWS stack (100% AWS), with the data lake on Snowflake
Design and hands-on build of solutions on AWS Bedrock — including prompt engineering, retrieval pipelines (RAG), and foundation model selection
Implement Bedrock Guardrails for content safety, PII handling, and accuracy thresholds
Ensure architectural alignment with Sallie Mae's existing MuleSoft investment and the planned MuleSoft Agent Fabric control-plane
Deliver agent layer code in SLM-preferred framework (LangChain / LangGraph or AWS Strands)
Drive eval-harness design covering agent accuracy, hallucination rates, and regression
Collaborate with VP, Technology Enablement, on the broader modernization roadmap
Own architecture decision records (ADRs) and engagement with the enterprise architecture function
Coordinate the future integration roadmap: CRM integration (Salesforce), omnichannel exposure (web + mobile), and IVR