Forward Deployed Engineer - Enterprise AI & Salesforce
VDart, Inc.
Dallas, TX, United States
15 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Applications Architecture
Audit Trail
Software Debugging
Log Analysis
Rapid Prototyping Process
Runbook
Salesforce.Com
SAP (Applications)
Systems Architecture
Systems Integration
+12 more
Enterprise Application Integration
Apex Code
Large Language Models
Multi-Agent Systems
Model Validation
Agentic-AI
Claude
Google Gemini
GPT
Mulesoft
Servicenow
Databricks
Job description
- We are seeking a strategic, AI-forward Forward Deployed Engineer to help enterprise clients understand, architect, and implement next-generation AI solutions across the Salesforce ecosystem. This role combines executive-level advisory, enterprise architecture, hands-on prototyping, and production stabilization.
- The ideal candidate will bridge business strategy and deep technical execution, guiding clients through enterprise AI adoption while translating emerging AI capabilities into practical, secure, scalable production solutions., * Advise client executives on frontier and open-weight models, AI agents, and Salesforceβs evolving AI ecosystem.
- Define enterprise AI strategies, technology roadmaps, solution architectures, and implementation approaches.
- Evaluate model selection based on accuracy, cost, latency, privacy, security, hosting, and operational requirements.
- Design agentic systems involving Agentforce, Data 360, Agent Fabric, external model platforms, retrieval, grounding, orchestration, memory, evaluation, and guardrails.
- Establish secure agent identity, delegated authority, least-privilege access, approval workflows, auditability, and revocation mechanisms.
- Architect Salesforce solutions and integrations across Agentforce, Data 360, MuleSoft, Databricks, SAP, ServiceNow, and other enterprise platforms.
- Develop prototypes, debug integrations, inspect code, analyze logs, and collaborate with engineers to validate solution behavior and resolve complex technical issues.
- Lead technical architecture decisions, escalations, production validation, and stabilization of enterprise AI solutions.
- Transition proven solutions to delivery and managed-services teams with architecture documentation, risk assessments, runbooks, and operational guidance.
- Develop reference architectures, publish technical thought leadership, and mentor architects and engineers on enterprise AI and agentic design.
Requirements
- 10+ years of experience delivering enterprise technology, platform, or architecture programs, including substantial Salesforce experience.
- Strong expertise in Salesforce architecture, security, data modeling, platform limitations, and enterprise integration patterns.
- Hands-on experience with at least one of Agentforce, Data 360, or MuleSoft, with working knowledge of the broader Salesforce ecosystem.
- Deep understanding of enterprise AI, LLMs, and agentic architectures, including GPT, Claude, Gemini, Llama, Nemotron, and Mistral.
- Experience with agent orchestration, tool use, retrieval-augmented generation (RAG), grounding, memory, evaluation, guardrails, and human oversight.
- Knowledge of model selection and trade-offs involving accuracy, cost, latency, privacy, sovereignty, hosting, and operational reliability.
- Understanding of enterprise AI security, including agent identity, delegated permissions, least-privilege access, policy enforcement, and auditability.
- Technical fluency in Apex, Lightning Web Components (LWC), Salesforce Flow, APIs, integration code, debugging, and log analysis.
- Experience taking enterprise AI or complex Salesforce platform solutions into production and supporting stabilization.
- Ability to engage with C-level executives while collaborating directly with architects and engineering teams.
- Strong communication, technical leadership, problem-solving, and stakeholder management skills., * Salesforce CTA, Application Architect, System Architect, Platform Developer, Agentforce, Data 360, or MuleSoft certifications.
- Experience with enterprise AI implementations across multiple industries and strategic client engagements.
- Published articles, conference presentations, reference architectures, or other thought leadership in enterprise AI, agentic systems, or Salesforce.
- Experience with AI-assisted development tools and modern AI engineering practices.
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