Sales Enablement GTM Engineer

GE HealthCare•Waukesha, WI

7d•$117,600 - $176,400•Hybrid

About The Position

Join a small, high-impact team building the next generation of AI-enabled commercial experiences using Salesforce, MuleSoft, and Agentic AI. We are looking for an engineer who can combine deep technical execution with an understanding of sales workflows to turn complex seller journeys into simple, intelligent experiences. GE HealthCare is a $20B publicly traded global med-tech company focused on diagnostic and digital solutions. With more than 50,000 employees across 160+ countries, GE HealthCare serves over 1 billion patients worldwide. Founded in 2023 as a spin-off from GE, we combine a strong heritage of innovation with the agility of a new growth-oriented public company.

Requirements

5+ years of software engineering or technical delivery experience, with at least 2 production AI, data engineering, or enterprise integration system deployed to production.
Fluent in Apex, or JavaScript, Agentforce script - and are willing to learn the others as needed.
Practical experience with API design (REST/SOAP/webhooks) and modern agent protocols (e.g., MCP, tool calling, or event-driven messaging architectures).
Expertise in process orchestration and API-led connectivity using tools like MuleSoft or custom middleware to bridge AI agents with legacy ERP systems.
Implemented secure service-to-service integration patterns (OAuth, SAML, event-driven architectures) and are conversant in emerging agent protocols like MCP and agent-to-agent communication.
Can implement secure data access and rigorously test it, including permissions, entitlements, consent, user context, restricted populations, and negative test cases.
Diagnose technical problems methodically, use logs and query evidence, isolate product behavior from configuration errors, and document a reproducible result.
Hands-on AI & Grounding Expertise: LLM orchestration, prompt tuning, and building knowledge base retrievers for enterprise data.
Working knowledge of enterprise B2B sales processes, including lead-to-opportunity, account and contact management, opportunity lifecycle, pipeline and forecasting, and sales execution workflows, with the ability to translate business processes into scalable Salesforce solutions.
Ability to understand Sales Rep and Sales Manager personas and translate commercial needs such as account preparation, opportunity progression, customer engagement, and next-best actions into intuitive, AI-enabled workflows that improve seller productivity.

Nice To Haves

Bachelor's degree in Computer Science or equivalent practical experience.
Relevant certifications in Salesforce Agentforce and Claude.
Experience within the Salesforce Ecosystem (Agentforce Specialist, Data Cloud, Apex, Flow, or Headless architectures).
Mulesoft Agentfabric experience.

Responsibilities

Configure and develop using Apex, Flow, Python, the REST Query API, Agentforce script, Lightning Actions and HXL as required - following security, change-management, and release controls.
Build, configure, and optimize complex operational workflows using AFO, defining agent reasoning, tool-calling logic, and conditional execution loops.
Implement modern agent-to-agent communication standards and the Model Context Protocol (MCP) to govern context sharing, task hand-offs, and tool execution across specialized AI agents.
Design, build, and maintain artifacts that ground Agentforce solutions in accurate, real-time enterprise data.
Implement robust, scalable, and secure data integration patterns that connect Agentforce to a wide range of enterprise applications and enable communication between AI agents.
Troubleshoot ingestion failures, mapping defects, schema drift, identity anomalies, query behavior, activation latency, API errors, permissions, and consumption issues - methodically, with logs and query evidence, isolating product behavior from configuration error.
Leverage modern AI tools (Claude, Kiro) embedded directly into your daily developer workflow to move from architecture sketch to deployable code in days, not months.