Senior AI Engineer - US East Coast, Remote

Cimpress/Vista • Boston, MA

134d

About The Position

AI Engineering is a new team being formed here at Vista to help drive enablement and adoption of Generative AI capabilities as well as build foundational primitives to help unlock productivity across the entire business. Engineers on this team will be leading the way for innovation in GenAI by helping us build capabilities at scale across all of our teams including MCP capabilities, LLM infrastructure and observability and agentic tooling.

Requirements

• Proven expertise in developing and scaling GenAI applications in production using modern frameworks similar to LlamaIndex or Langraph that leverage various workflows like RAG, Multi-Agent or similar architectures
• A strong understanding of the advantages and limitations of different LLM models and providers to help guide optimal integration to our applications
• Experience building web based application in Python at scale in production
• Deep understanding of GenAI primitives like vector databases, memory, semantic search, hybrid search, agentic workflows and patterns, MCP, A2A
• Ability to drive a long term technical roadmap, establish standards and evangelize those standards Engineering wide
• Knowledge of how to build, scale and deploy applications in AWS using systems like ECS, Fargate and EKS, ideally with IaC
• Experience integrating the AWS Bedrock ecosystem of tools into GenAI applications like Bedrock, Guardrails, Evaluations and Agents
• Strong communication skills and ability to partner with other Engineering leaders

Nice To Haves

• Experience working in Typescript in production at scale
• Ability to help build and scale organization wide GenAI evaluation frameworks helping teams understand the efficacy of their applications
• Implementation of LLM observability tools
• Experience building and integrating MCP servers to AI applications, particularly with AuthZ and AuthN requirements

Responsibilities

• Support the newly formed team of AI Engineers driving strategic design, adoption and implementation of large scale GenAI initiatives
• Build and scale reusable platform components like AI Gateways, python and typescript SDKs, MCP capabilities, RAG pipelines, LLM frameworks, vector databases and other primitives enabling teams to build GenAI applications at scale with great tooling
• Create and influence engineering wide standards for GenAI, and partner with existing Engineering teams to help drive adoption
• Build and launch reusable automation workflow capabilities company wide to drive transformation of GenAI adoption across all business functions

What This Job Offers

• Number of Employees: 5,001-10,000 employees