> Markdown version of [/jobs/ext/1424465-forward-deployment-engineer-ai-agentic-engineer-ct-tx](https://www.wearedevelopers.com/jobs/ext/1424465-forward-deployment-engineer-ai-agentic-engineer-ct-tx). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

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# Forward Deployment Engineer AI Agentic Engineer CT & TX

- **Company:** Ipolarity LLC
- **Location:** Hanover, NJ, United States
- **Salary:** $114,400.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Information Engineering, Cursor (Graphical User Interface Elements), Software Debugging, Software Design Patterns, Node.Js, Software Architecture, Tableau (Software), TypeScript, ReactJS, Large Language Models, Backend, Event Driven Architecture, Graphql, Front End Software Development, Streamlit Framework, Data Pipelines, Databricks
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=97db7cca45ac78b2

## About the Role

AI/LLM: Claude, Cursor, Codex, Anthropic/OpenAI APIs, Prompting, Tool Use, Agent Patterns, MCP.
Frontend: React, TypeScript.
Backend: Python or Node.js, REST/GraphQL APIs, Event-Driven Architecture.
Data: Databricks, PySpark, Delta Lake, Notebooks, Workflows.
Cloud: AWS - S3, Lambda, Glue, Redshift.
IaC: Infrastructure-as-Code experience preferred.
Visualization: Streamlit, Tableau, or Evidence is a plus.

## Description

We are looking for a hands-on Forward Deployment Engineer who can build and ship production-grade AI agents and automation solutions using an AI-native development approach.
What You'll Do

 * Build and deploy AI agents using tool/function calling, multi-turn context, MCP, and agentic design patterns.

 * Use Claude, Cursor, and Codex as part of your daily development workflow.

 * Evaluate and validate non-deterministic LLM output and ensure production-quality results.

 * Take solutions from concept to production with minimal handoffs.

 * Build across frontend, backend, data engineering, and cloud infrastructure

 * Design AI-assisted workflows and reusable agent skills for engineering teams.

 * Build data pipelines and analytical solutions using Databricks and AWS.

Partner directly with Product Managers and business stakeholders.

 * Make architectural decisions around AI/LLM-based solutions vs. deterministic approaches.


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