Senior Software Engineer, Data

ITX Corp.

Senior Software Engineer with Data Skills for AI systems. Focus on building infrastructure for LLM-powered applications and agent-based systems.

Posted 7/31/2026full-timeRemote • New York • 🇺🇸 United StatesMid-LevelSenior💰 $96,000 - $129,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining ETL pipelines for unstructured data, developing agent-based architectures, and implementing memory systems for LLM applications. Proficient in creating evaluation tests and ensuring safe interactions within AI-powered systems.

Highest-signal resume keywords

ETL Pipeline DevelopmentAgent-Based Architecture DesignLLM System InteractionWorkflow Orchestration FrameworksAgent Memory System Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL WorkflowsRAG PipelinesAgent ArchitecturesPrompt DesignPerformance TestingEvaluation Dataset GenerationUser Intent MappingGuardrails ImplementationDocument ProcessingData Pipeline Management

Soft Skills

CollaborationGuidance

Tools & Technologies

LangGraphAWS CLIAWS STS

Industry Keywords

Unstructured DataAI-Powered ApplicationsAgent WorkflowsPrompt SecurityUser-Generated Content Handling

Tech Stack

Tools & technologies

AWSETLNode.jsReact

About the role

Key responsibilities & impact

Design and maintain ETL pipelines that process and classify unstructured data for RAG systems
Support the development of agent-based architectures using reasoning and acting patterns such as ReAct
Build and maintain agent workflows using node-based orchestration frameworks such as LangGraph
Design and implement agent memory systems, including short-term event memory and long-term memory strategies
Develop system prompts and intent-handling prompts that support reliable agent interactions
Create evaluation tests, datasets, and performance benchmarks for LLM agent behavior
Build tools that allow LLM agents to interact with external systems and services
Apply best practices around guardrails, prompt security, input sanitization, and safe handling of user-generated content
Collaborate closely with engineers and provide guidance to less experienced developers when needed

Requirements

What you’ll need

Experience building RAG pipelines or ETL workflows for unstructured documents
Experience working with LLM-based systems or AI-powered applications
Familiarity with agent architectures such as ReAct
Hands-on experience with workflow orchestration frameworks such as LangGraph or similar node-based systems
Experience implementing agent memory systems, including both short-term and long-term memory strategies
Experience writing system prompts and designing prompt interactions for LLM applications
Experience evaluating and performance testing LLM agents
Ability to generate evaluation datasets and test scenarios for agent-based systems
Understanding of mapping user utterances to intents using RAG or LLM-based approaches
Understanding of guardrails and safety mechanisms for LLM and agent systems
Understanding of agent-specific threat vectors, including prompt injection, tool misuse, and unsafe memory access
Familiarity with AWS environments and tools such as AWS CLI and STS
Strong understanding of data pipelines and document processing for AI systems

Benefits

Comp & perks

Market-based pay adjustments at least once a year
Pay reviews based on market data