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Nateravia Greenhouse

AI Architect, Salesforce

Austin, TXPosted 3mo ago
OtherLeadFull-time

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About the Role

The Opportunity

We are seeking a visionary Senior AI Architect to pioneer the integration of cutting-edge AI solutions across our Salesforce CRM ecosystem and AWS cloud infrastructure. This is a strategic, high-impact role where you'll architect and implement Generative AI applications that transform how we engage with patients, automate complex workflows, and unlock predictive insights from our data.

You'll serve as our technical authority on the convergence of Salesforce Data Cloud, Einstein Trust Layer, and Amazon Bedrock, moving beyond simple integrations to build sophisticated "Bring Your Own Model" (BYOM) architectures that are secure, scalable, and measurably impactful.

What You'll Do

AI Strategy & Architecture (40%)

  • Define end-to-end architecture for Generative AI solutions, integrating Salesforce Data Cloud with Amazon Bedrock and SageMaker
  • Design "Bring Your Own Model" (BYOM) patterns that enable Salesforce to securely access foundational models (Claude, Titan, Llama 2) hosted on AWS via Bedrock
  • Architect data ingestion and grounding strategies using RAG (Retrieval Augmented Generation) to ensure AI models have real-time access to unified customer and patient profiles
  • Establish comprehensive AI governance frameworks ensuring compliance with Einstein Trust Layer standards, including data privacy, zero-data retention policies, and PII masking

Implementation & Development (30%)

  • Lead technical implementation of Model Builder and Prompt Builder within Salesforce, connecting them to external AWS endpoints
  • Configure Amazon Bedrock agents and knowledge bases to execute complex tasks and retrieve proprietary data for business users
  • Develop serverless middleware using AWS Lambda and API Gateway to enable low-latency communication between Salesforce Flow/Apex and AWS inference endpoints
  • Oversee fine-tuning of models on AWS SageMaker when out-of-the-box Bedrock models require domain-specific adaptation for healthcare use cases

Cross-Functional Collaboration (20%)

  • Partner with Data Engineers to ensure Salesforce Data Cloud correctly ingests, harmonizes, and activates data streams from S3, Redshift, and other enterprise sources
  • Collaborate with Salesforce Administrators and Developers to embed AI outputs directly into workflows (Service Console, Lightning Web Components, etc.)
  • Serve as the AI subject matter expert for Product Managers, translating "AI buzzwords" into viable technical roadmaps and realistic, measurable deliverables
  • Work closely with Business Systems leadership to align AI initiatives with strategic transformation goals

Optimization & Innovation (10%)

  • Monitor LLM performance metrics including latency, accuracy, and token costs; implement caching strategies and intelligent model selection logic to optimize spend
  • Stay ahead of rapid evolution in the Salesforce/AWS partnership, evaluating and piloting new capabilities like Zero Copy Data Sharing and Vector Database integrations
  • Drive continuous improvement through A/B testing, performance benchmarking, and user feedback loops

What You'll Bring

Required Technical Expertise

AWS AI/ML Stack:

  • Deep, hands-on expertise in Amazon Bedrock (mandatory)
  • Proven experience configuring Bedrock Knowledge Bases, Agents, and Guardrails
  • Proficiency with AWS Lambda, API Gateway, IAM, and security best practices for cross-cloud access
  • Working knowledge of AWS SageMaker for model training and deployment

Salesforce AI Stack:

  • Strong working knowledge of Salesforce Data Cloud and Einstein 1 Platform
  • Experience with Model Builder and Prompt Builder setup and configuration
  • Understanding of Salesforce Service Cloud and Sales Cloud architecture

Architecture & Integration:

  • Demonstrated experience designing RAG (Retrieval Augmented Generation) architectures
  • Experience with Vector Database integrations (OpenSearch Serverless, Pinecone, or similar)
  • Expert-level knowledge of REST/gRPC APIs, OAuth 2.0 flows, and named credentials for secure Salesforce-to-AWS connectivity

Programming:

  • Proficiency in Python (AWS Lambda, Boto3, data processing)
  • Familiarity with Apex for Salesforce triggers, callouts, and custom logic
  • Experience with Infrastructure as Code (Terraform, CloudFormation) is a plus

Experience Requirements

  • 8+ years of experience in Enterprise Architecture, Cloud Engineering, or Data
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