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# Forward Deployed Engineer

- **Company:** National Computer Systems
- **Location:** Piscataway, NJ, United States
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Databases, Customer Data Management, Information Engineering, Software Debugging, SQL Databases, TypeScript, Enterprise Data Management, ReactJS, Large Language Models, Multi-Cloud, HR Software, Pyspark, Kubernetes, Terraform, Data Pipelines
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bf8129ee55506ca5

## About the Role

Strong software engineering fundamentals - you can design, build, debug, and ship production systems end to end.
Hands-on experience with LLM applications: RAG, agents, tool/function calling, prompt and context engineering, evaluation.
Data engineering competence: pipelines, SQL, data modeling; PySpark or similar a plus.
Full-stack ability to stand up usable applications quickly (TypeScript/React or similar).
Comfort operating in ambiguity at a customer site - extracting requirements from real users, making scoping calls, and defending technical decisions to non-engineers.
Bias for shipping: you'd rather demo something real in ten days than perfect something in three months.
Excellent communication; you will be the face of the team at the customer.
Nice to have
Kubernetes/Helm/Terraform familiarity; experience deploying in restricted or air-gapped environments.
Experience with AI coding agents/harnesses (Claude Code or similar) used for production-grade development.
Ontology, knowledge-graph, or enterprise data-platform experience.
Enterprise domain exposure: supply chain, CRM, HR systems, e-commerce, or manufacturing.

## Description

Embed on-site or deeply with customer teams; map their most painful workflows with your Deployment Strategist partner and turn them into shipped software.
Build data pipelines (e.g., PySpark) connecting customer source systems - ERP, CRM, databases, documents - with quality, lineage, and row/column-level permissions.
Model customer data as an executable ontology (Objects · Properties · Links · Actions) and prepare it for AI consumption (vector indexes, retrieval sources).
Build RAG-grounded agents and applications (e.g., TypeScript) that don't just answer - they act, writing back to real systems via tool-calling.
Run fast validation loops with business users: weekly iterations, evaluation, guardrail tuning, go/no-go.
Harden and deploy to production with the Core-Dev team - multi-cloud (AWS/Azure/GCP) or fully on-premises/air-gapped.
Deliver AI-driven software builds (new applications, SaaS replacements, migrations) using our AI-development harness - orchestrating specialist AI agents through a gated lifecycle rather than hand-writing every line.
Feed what you learn back to HQ: patterns you validate in the field become standard platform components.


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