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Entry Level Retrieval Augmented Generation Jobs in Rochester, NY

Entry Level Retrieval Augmented Generation information

What is an entry level retrieval augmented generation job?

Entry level retrieval augmented generation jobs involve assisting in the development and optimization of AI systems that combine information retrieval techniques with generative models. Employees in these roles typically help build, test, and maintain systems where AI retrieves relevant data from large databases to enhance the accuracy and relevance of generated responses. These positions often require basic skills in programming, machine learning, and familiarity with natural language processing. They are ideal for recent graduates or those new to AI, offering opportunities to learn about modern AI architectures and contribute to innovative projects. Entry level workers may work under the guidance of senior engineers or researchers, supporting experimentation and evaluation tasks.

What are the key skills and qualifications needed to thrive as an entry level retrieval augmented generation specialist?

To thrive as an Entry Level Retrieval Augmented Generation Specialist, you need a foundational understanding of natural language processing (NLP), information retrieval, and basic programming skills, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, vector databases (like FAISS or Pinecone), and frameworks for large language models (LLMs) is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate and troubleshoot solutions in team environments. These skills and qualities are crucial for building reliable RAG systems that deliver accurate and relevant information to users.

What is the difference between Entry Level Retrieval Augmented Generation vs Entry Level Data Scientist?

AspectEntry Level Retrieval Augmented GenerationEntry Level Data Scientist
Required CredentialsBasic programming, understanding of NLP and AI conceptsBachelor's in Data Science, Computer Science, or related field
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Industry UsageAI development, NLP applications, chatbot creationData analysis, predictive modeling, data-driven decision making

Entry Level Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with generative AI, requiring knowledge of NLP and programming. Entry Level Data Scientist involves analyzing data, building models, and deriving insights, often with a broader data analysis skill set. While both roles require technical skills, Retrieval Augmented Generation is more specialized in AI model development, whereas Data Scientists work across various data projects.

What are some common challenges faced by entry-level professionals working in retrieval augmented generation roles?

Entry-level professionals in Retrieval Augmented Generation (RAG) often encounter challenges such as understanding how to effectively combine information retrieval systems with large language models and adapting to rapidly evolving technologies. Balancing accuracy and efficiency when designing or fine-tuning retrieval pipelines can also be a learning curve. Additionally, you may need to collaborate closely with data engineers, machine learning specialists, and product teams to ensure the RAG system aligns with business requirements. Staying proactive in learning and engaging with peers can help overcome these challenges and accelerate career growth.
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Infographic showing various Entry Level Retrieval Augmented Generation job openings in Rochester, NY as of August 2026, with employment types broken down into 70% Full Time, 28% Part Time, and 2% Contract. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution.

SR Software Engineer (Data) - Remote, US

ITX Corp

Rochester, NY • On-site, Remote

$96K - $129K/yr

Full-time

Re-posted 9 days ago


Job description

Join Our Team as a Senior Software Engineer with Data Skills for Agentic AI Systems!
We are looking for a Senior Software Engineer with a strong focus on Data and experience building infrastructure for LLM-powered applications and agent-based systems. In this role, you will work on RAG pipelines, agent workflows, and memory systems that allow AI agents to reason, retrieve information, and interact with complex tasks.
You will collaborate with engineers building intelligent agents and help design the data pipelines, evaluation frameworks, and orchestration workflows that support reliable and scalable AI systems.
Note: This opening is only available for candidates based in the United States of America. Applications from other locations will not be considered for the role.
What You'll Do:
  • Design and maintain ETL pipelines that process and classify unstructured data for Retrieval-Augmented Generation (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, including hierarchical and state-machine-based execution.
  • Design and implement agent memory systems, including short-term event memory and long-term memory strategies such as summarization, semantic memory, episodic memory, and user preference storage.
  • Develop system prompts and intent-handling prompts that support reliable agent interactions.
  • Create evaluation tests, datasets, and performance benchmarks to measure and improve LLM agent behavior, including ReAct-based agents.
  • 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 across the team and provide guidance to less experienced developers when needed.

What We're Looking For:
  • 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 (e.g., AgentCore Memory API or similar), including both short-term and long-term memory strategies.
  • Experience writing system prompts and designing prompt interactions for LLM applications, including intent handling.
  • Experience evaluating and performance testing LLM agents, particularly within ReAct-style workflows.
  • Ability to generate evaluation datasets and test scenarios for agent-based systems.
  • Understanding of mapping user utterances to intents using RAG and/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.

Nice to have:
  • Experience with LangGraph or other agent orchestration frameworks.
  • Experience building tools for tool-enabled LLM agents.
  • Experience working with hierarchical state machines or complex workflow orchestration patterns.
  • Experience designing evaluation frameworks or LLM benchmarking systems.
  • Experience working with AI agent security concepts or threat modeling.

ITX's Compensation Philosophy
Equality in compensation has been our practice since ITX started, in 1997.
ITX believes that market-based pay ensures fair and equitable compensation for our worldwide team members and pay that is based on the market, not on who has the best negotiation skills. At ITX, you'll never discover that someone in the same job with the same experience makes more than you, or that there are pay gaps based on race, gender, disability, or age.
How do our team members experience market-based pay at ITX? We gather market data to benchmark each position in our candidates' and team members' locations and use these benchmarks for candidate offers and to perform regular compensation reviews for our team members. You'll never have to worry about asking for a pay raise again. At least once a year ITX automatically adjusts pay when the benchmark is higher than our team member's compensation.
In Rochester, N.Y., home to ITX's headquarters, the pay range for a Senior Software Developer with Data Skills role is $96,000 to $129,000, depending on experience, specific skills and certifications, and education. Based on your location in the United States if you are in a place where the market for your role is higher or lower, this pay range could be 13% lower or 10% higher than the Rochester, N.Y. market.
ITX has team members in many countries, and we use the same methodology for determining pay for all our teammates. For candidates outside of the United States, we use local market data to determine the benchmark range for the Senior Software Engineer with Data Skills.
Do you have questions about ITX's compensation practices? Let us know! We're proud of how we do compensation at ITX and welcome the opportunity to share more.
This role was posted by ITX on June 30th, 2026.