Business Systems Automation Engineer

CentralReach•Holmdel Township, NJ

2d•$100,000 - $125,000•Hybrid

About The Position

CentralReach is building an intelligent CRM platform that combines language models, automated workflows, and structured business data. The Business Systems Automation Engineer designs and deploys systems that turn natural language into business actions, connecting live LLM pipelines with Salesforce-powered operations and production CRM systems. The role develops multi-step AI automation and integrations, engineers reasoning and evaluation layers, and helps scale automation across the business. It also collaborates with Tableau and Salesforce stakeholders to translate model outputs into useful business signals, insights, dashboards, and reporting that support revenue operations and pipeline visibility. The role emphasizes demonstrated ability over credentials.

Requirements

Ability to build end-to-end, multi-step AI workflows that trigger model calls, route outputs, and update downstream platforms without manual handoffs.
Ability to connect LLM APIs to Salesforce objects and flows, pull live CRM context into prompts, and write structured outputs back to Salesforce.
Experience engineering prompts systematically, including few-shot design and output validation, and evaluating retrieval quality and business-aligned outcomes.
Understanding of knowledge-based AI and ontology design, including defining entity types, relationships, and semantic hierarchies so AI pipelines can reason over real-world information.

Nice To Haves

Exposure to revenue operations workflows, pipeline reporting, or CRM-driven business processes.
Experience working with Tableau or Salesforce dashboards in a cross-functional analytics context.
Ability to frame AI outputs in terms of business value, such as lead conversion, churn reduction, or process efficiency.
Experience with technologies such as Python, SQL, LLM APIs (OpenAI, Anthropic, or HuggingFace), Salesforce REST API, Flows and Objects, RAG frameworks (LangChain or LlamaIndex), vector databases (FAISS, Pinecone, or Weaviate), ontology or semantic modeling (RDF, OWL, SKOS or equivalent), workflow orchestration platforms (N8N, Airflow or equivalent), MLOps or managed AI infrastructure (Shakudo, SageMaker or equivalent), Tableau, ETL/data pipeline tooling, and Git.
Examples of relevant work may include building a chatbot or assistant connected to a live data system; designing a RAG pipeline structured around business entities; creating evaluation logic for output quality, relevance, and business alignment; or modeling information flows in which entity relationships shape reasoning or retrieval.

Responsibilities

Design and deploy multi-step AI automation flows connecting LLM inference, CRM triggers, webhook events, and data transformations across integrated systems.
Build and maintain full-stack integrations between large language model APIs and Salesforce, dynamically reading CRM context into model prompts and writing outputs to Salesforce objects and flows.
Engineer prompt templates, few-shot frameworks, and output validation logic to meet business-defined quality standards.
Develop and run LLM evaluation pipelines using frameworks such as RAGAS, TruLens, or equivalent, measuring model performance against business outcomes.
Collaborate with Tableau and Salesforce stakeholders to surface AI-driven insights through dashboards and reporting workflows.
Translate technical model outputs into interpretable business signals to support revenue operations and pipeline visibility.