Software Engineer - AI/RAG
Addison, TX · On-site
InterSources Inc is focused on developing reusable toolkits for Gen AI RAG capabilities. The role involves designing, building, and operating software solutions while ensuring compliance and ...
Software Engineer - AI/RAG
Addison, TX · On-site
InterSources Inc is focused on developing reusable toolkits for Gen AI RAG capabilities. The role involves designing, building, and operating software solutions while ensuring compliance and ...
AI Engineer
Dallas, TX · On-site
Contract Key Skills - AI, Python, Rag, LLM Overview We are seeking an AI Engineer with proven experience in building and scaling AI-powered applications . This role combines hands-on development with ...
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AI Engineer
Dallas, TX · On-site
Contract Key Skills - AI, Python, Rag, LLM Overview We are seeking an AI Engineer with proven experience in building and scaling AI-powered applications . This role combines hands-on development with ...
The ideal candidate should have strong expertise in LLMs, Agentic AI, RAG, LangChain/LangGraph, Python, FastAPI, Azure OpenAI, AWS, and cloud-native AI architectures. Required Skills 11+ years in AI ...
New
The ideal candidate should have strong expertise in LLMs, Agentic AI, RAG, LangChain/LangGraph, Python, FastAPI, Azure OpenAI, AWS, and cloud-native AI architectures. Required Skills 11+ years in AI ...
New
AI Engineer
Fort Worth, TX · On-site
$114K - $150K/yr
Implement Graph RAG solutions by integrating knowledge graphs, entity extraction, relationship ... Deploy AI workloads on AWS, Azure, and GCP , using services such as Bedrock, SageMaker, Azure ...
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AI Engineer
Fort Worth, TX · On-site
$114K - $150K/yr
Implement Graph RAG solutions by integrating knowledge graphs, entity extraction, relationship ... Deploy AI workloads on AWS, Azure, and GCP , using services such as Bedrock, SageMaker, Azure ...
Forward Deployed Engineer
Richardson, TX · On-site
RAG * Agentic AI / Multi-Agent Systems * MCP (Model Context Protocol) * Production deployment experience * End-to-end ownership (Discovery → Production)
Forward Deployed Engineer
Richardson, TX · On-site
RAG * Agentic AI / Multi-Agent Systems * MCP (Model Context Protocol) * Production deployment experience * End-to-end ownership (Discovery → Production)
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
Enterprise AI Architect
Dallas, TX · Remote
$70.75 - $91/hr
Generative AI, Agentic AI, RAG, AI Agents * AI orchestration frameworks (such as LangChain or LangGraph) * Vector databases and knowledge retrieval * AI governance, security, and Responsible AI
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Enterprise AI Architect
Dallas, TX · Remote
$70.75 - $91/hr
Generative AI, Agentic AI, RAG, AI Agents * AI orchestration frameworks (such as LangChain or LangGraph) * Vector databases and knowledge retrieval * AI governance, security, and Responsible AI
AI Intern - Dallas, TX
Plano, TX · On-site
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
AI Intern - Dallas, TX
Plano, TX · On-site
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
AI Engineer Intern - USA
Plano, TX · On-site
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
AI Engineer Intern - USA
Plano, TX · On-site
Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data. * Develop and test AI agents, traditional ML models, and deterministic logic for real-world use ...
Enterprise AI Architect
$68.25 - $88/hr
Generative AI, Agentic AI, RAG, AI Agents * AI orchestration frameworks (such as LangChain or LangGraph) * Vector databases and knowledge retrieval * AI governance, security, and Responsible AI
Enterprise AI Architect
$68.25 - $88/hr
Generative AI, Agentic AI, RAG, AI Agents * AI orchestration frameworks (such as LangChain or LangGraph) * Vector databases and knowledge retrieval * AI governance, security, and Responsible AI
RAG (Retrieval-Augmented Generation) Establish best practices for prompt engineering, agent memory, tool usage, context management, reasoning, and AI governance. Lead technical decision-making for ...
RAG (Retrieval-Augmented Generation) Establish best practices for prompt engineering, agent memory, tool usage, context management, reasoning, and AI governance. Lead technical decision-making for ...
Senior AI Engineer - Talent Community
Richardson, TX · On-site
$94K - $130K/yr
Lead the end-to-end design, development, and implementation of scalable AI/ML systems and pipelines, emphasizing Generative AI/LLM solutions, including RAG implementation and evaluation.
Senior AI Engineer - Talent Community
Richardson, TX · On-site
$94K - $130K/yr
Lead the end-to-end design, development, and implementation of scalable AI/ML systems and pipelines, emphasizing Generative AI/LLM solutions, including RAG implementation and evaluation.
Enterprise AI Architect
Dallas, TX · On-site +1
$68.25 - $88/hr
Generative AI, Agentic AI, RAG, AI Agents * AI orchestration frameworks (such as LangChain or LangGraph) * Vector databases and knowledge retrieval * AI governance, security, and Responsible AI
Enterprise AI Architect
Dallas, TX · On-site +1
$68.25 - $88/hr
Generative AI, Agentic AI, RAG, AI Agents * AI orchestration frameworks (such as LangChain or LangGraph) * Vector databases and knowledge retrieval * AI governance, security, and Responsible AI
AI Solutions Lead
Irving, TX · Hybrid
Hands-on delivery of AI, machine learning, generative AI, RAG, automation, or agentic solutions - building, not only advising (Experience as a Forward Deployed Engineer, Customer Engineer, or ...
AI Solutions Lead
Irving, TX · Hybrid
Hands-on delivery of AI, machine learning, generative AI, RAG, automation, or agentic solutions - building, not only advising (Experience as a Forward Deployed Engineer, Customer Engineer, or ...
Drive adoption of AI-enabled, agentic, and cloud-native architectures, including AI/ML, RAG, LLM integration, reasoning models, and intelligent workflow orchestration to improve automation ...
Drive adoption of AI-enabled, agentic, and cloud-native architectures, including AI/ML, RAG, LLM integration, reasoning models, and intelligent workflow orchestration to improve automation ...
Snowflake Architect- Cortex
Dallas, TX · On-site
$120 - $160/hr
You will act as a trusted technical advisor, translating customer business problems into scalable Cortex -powered solutions spanning generative AI, RAG, LLM functions, and ML workflows. Key ...
Snowflake Architect- Cortex
Dallas, TX · On-site
$120 - $160/hr
You will act as a trusted technical advisor, translating customer business problems into scalable Cortex -powered solutions spanning generative AI, RAG, LLM functions, and ML workflows. Key ...
Senior Cloud Engineer AI
Dallas, TX · On-site
$81K - $151K/yr
Azure Machine Learning, Azure OpenAI, Azure AI Foundry Experience building MLOps platforms and automated ML pipelines Strong knowledge of LLMOps, LLM lifecycle management, agentic AI, RAG (retrieval ...
Senior Cloud Engineer AI
Dallas, TX · On-site
$81K - $151K/yr
Azure Machine Learning, Azure OpenAI, Azure AI Foundry Experience building MLOps platforms and automated ML pipelines Strong knowledge of LLMOps, LLM lifecycle management, agentic AI, RAG (retrieval ...
Lead AI Engineer - Agentic & Generative AI
Richardson, TX · On-site
$98K - $129K/yr
RAG & Vector Databases * LangGraph, Agents SDK, Google ADK * Docker, Kubernetes, CI/CD * AWS, Azure, or GCP * AI Governance & Observability * Cursor, Windsurf, Codex Key Responsibilities * Define AI ...
Lead AI Engineer - Agentic & Generative AI
Richardson, TX · On-site
$98K - $129K/yr
RAG & Vector Databases * LangGraph, Agents SDK, Google ADK * Docker, Kubernetes, CI/CD * AWS, Azure, or GCP * AI Governance & Observability * Cursor, Windsurf, Codex Key Responsibilities * Define AI ...
Senior AI Engineer
Dallas, TX · On-site
$180 - $260/hr
Develop and deploy LLM‑powered applications using RAG, fine‑tuning, prompt engineering, function calling, and tool use. * Implement guardrails, evaluation frameworks, and responsible AI controls ...
Senior AI Engineer
Dallas, TX · On-site
$180 - $260/hr
Develop and deploy LLM‑powered applications using RAG, fine‑tuning, prompt engineering, function calling, and tool use. * Implement guardrails, evaluation frameworks, and responsible AI controls ...
Ai Rag information
See Lancaster, TX salary details
$30.3K - $34.8K
5% of jobs
$34.8K - $39.2K
5% of jobs
$39.2K - $43.7K
6% of jobs
$46.3K is the 25th percentile. Wages below this are outliers.
$43.7K - $48.1K
14% of jobs
$48.1K - $52.5K
11% of jobs
The median wage is $54.4K / yr.
$52.5K - $57K
21% of jobs
$60.9K is the 75th percentile. Wages above this are outliers.
$57K - $61.4K
15% of jobs
$61.4K - $65.8K
11% of jobs
$65.8K - $70.3K
4% of jobs
$70.3K - $74.7K
5% of jobs
$74.7K - $79.2K
3% of jobs
$30.3K
$55.2K
$79.2K
How much do ai rag jobs pay per year?
As of Aug 8, 2026, the average yearly pay for ai rag in Lancaster, TX is $55,217.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,500.00 and $61,600.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as an AI researcher?
To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.
What is the difference between Ai Rag vs Data Analyst?
| Aspect | Ai Rag | Data Analyst |
|---|---|---|
| Required Credentials | Typically a diploma or certification in AI, machine learning, or related fields | Bachelor's degree in statistics, mathematics, or related fields |
| Work Environment | Tech companies, AI startups, research labs | Business, finance, healthcare, and various industries |
| Employer & Industry Usage | Primarily in AI development and research | Across industries for data interpretation and decision-making |
| Common Search & Comparison | Yes | Yes |
Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.
What is an AI RAG?
AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.
What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?
AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What cities near Lancaster, TX are hiring for Ai Rag jobs? Cities near Lancaster, TX with the most Ai Rag job openings:
Job description
Job Summary:
InterSources Inc is focused on developing reusable toolkits for Gen AI RAG capabilities. The role involves designing, building, and operating software solutions while ensuring compliance and maintainability, as well as mentoring other engineers in CI/CD practices.
Responsibilities:
• Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
• Designs, develops, and modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained
• Mentors other software engineers and coach team on Continuous Integration and Continuous Development (CI-CD) practices and automating tool stack
• Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle
• Performs spike/proof of concept as necessary to mitigate risk or implement new ideas
• Automates manual release activities
• Designs, develops, and maintains automated test suites (integration, regression, performance)
• Performs Continuous Integration and Continuous Development (CI-CD) activities.
• Contributes to story refinement and definition of requirements.
• Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle.
• Manage multiple priorities, and simultaneously engage with multiple teams.
• Be vocal and actively participate in all session with business stakeholders and agile teams.
• Collaborate with product teams, data analysts and data scientists to design and build solutions.
• Utilizes multiple architectural components (across data, application, business) in design and development of client requirements.
Qualifications:
Required:
• 5 years of relevant experience required.
• Experience in Semantic Search, data processing, Data & Analytics, Data pipeline.
• Experience in OOP in Python/Scala/Java programming experience with expert level development skills.
• Hands on experience and knowledge generative AI RAG process for various use cases, including chunking, embedding, retrieval, reranking and summarization.
• Hands-on experience in application development in one or more areas MongoDB, Redis, Angular/React Frameworks, Containerization, Building API based application leveraging FAST API services, JWT Integration, API Gateway.
• Develop efficient utilities, automation frameworks, data science platforms that can be utilized across multiple Data Science teams for AI/ML and GenAI work.
• Experience with AI/ML/GenAI Lifecycle Management and Development and its Ecosystem. Hands on experience building frameworks using MLOps, Fine – Tuning techniques, Inference Frameworks.
• Building API based application leveraging FAST API services, JWT Integration, API Gateway.
• Working in large sized teams that collaboratively develop on a shared multi-repo codebase using IDEs (e.g. VS Code rather than Jupyter Notebooks), Continuous Integration (CI), Continuous Deployment (CD) and Continuous Testing.
• Hands-on DevOps experience with one or more of the following enterprise development tools: Version Control (GIT/Bitbucket), Build Orchestration (Jenkins), Code Quality (SonarQube and pytest Unit Testing), Artifact Management (Artifactory) and Deployment (Ansible).
Preferred:
• Experience developing Gen AI training and RAG platform with open-source model, inferencing & servicing capabilities, MCP modules etc.
Company:
InterSources Inc. solves operational problems where protection, performance, compliance, AI, and workforce capability must work together. Founded in 2007, the company is headquartered in Fremont, USA, with a team of 501-1000 employees. The company is currently Late Stage.
InterSources Inc is focused on developing reusable toolkits for Gen AI RAG capabilities. The role involves designing, building, and operating software solutions while ensuring compliance and maintainability, as well as mentoring other engineers in CI/CD practices.
Responsibilities:
• Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
• Designs, develops, and modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained
• Mentors other software engineers and coach team on Continuous Integration and Continuous Development (CI-CD) practices and automating tool stack
• Executes story refinement, definition of requirements, and estimating work necessary to realize a story through the delivery lifecycle
• Performs spike/proof of concept as necessary to mitigate risk or implement new ideas
• Automates manual release activities
• Designs, develops, and maintains automated test suites (integration, regression, performance)
• Performs Continuous Integration and Continuous Development (CI-CD) activities.
• Contributes to story refinement and definition of requirements.
• Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle.
• Manage multiple priorities, and simultaneously engage with multiple teams.
• Be vocal and actively participate in all session with business stakeholders and agile teams.
• Collaborate with product teams, data analysts and data scientists to design and build solutions.
• Utilizes multiple architectural components (across data, application, business) in design and development of client requirements.
Qualifications:
Required:
• 5 years of relevant experience required.
• Experience in Semantic Search, data processing, Data & Analytics, Data pipeline.
• Experience in OOP in Python/Scala/Java programming experience with expert level development skills.
• Hands on experience and knowledge generative AI RAG process for various use cases, including chunking, embedding, retrieval, reranking and summarization.
• Hands-on experience in application development in one or more areas MongoDB, Redis, Angular/React Frameworks, Containerization, Building API based application leveraging FAST API services, JWT Integration, API Gateway.
• Develop efficient utilities, automation frameworks, data science platforms that can be utilized across multiple Data Science teams for AI/ML and GenAI work.
• Experience with AI/ML/GenAI Lifecycle Management and Development and its Ecosystem. Hands on experience building frameworks using MLOps, Fine – Tuning techniques, Inference Frameworks.
• Building API based application leveraging FAST API services, JWT Integration, API Gateway.
• Working in large sized teams that collaboratively develop on a shared multi-repo codebase using IDEs (e.g. VS Code rather than Jupyter Notebooks), Continuous Integration (CI), Continuous Deployment (CD) and Continuous Testing.
• Hands-on DevOps experience with one or more of the following enterprise development tools: Version Control (GIT/Bitbucket), Build Orchestration (Jenkins), Code Quality (SonarQube and pytest Unit Testing), Artifact Management (Artifactory) and Deployment (Ansible).
Preferred:
• Experience developing Gen AI training and RAG platform with open-source model, inferencing & servicing capabilities, MCP modules etc.
Company:
InterSources Inc. solves operational problems where protection, performance, compliance, AI, and workforce capability must work together. Founded in 2007, the company is headquartered in Fremont, USA, with a team of 501-1000 employees. The company is currently Late Stage.
About InterSources
Sourced by ZipRecruiter
In 2007, Our journey began as pioneers in the realm of technology and security. Since then, InterSources Inc. has evolved into a trusted partner, leading the way in Cloud Security, Cybersecurity, PLG Consulting, Digital Transformation, and Professional Services. With a rich history of excellence and a forward-thinking approach, we continue to secure your digital future and drive innovation. Explore our legacy of success and discover the possibilities that lie ahead.
Company size
51 - 200 Employees
Headquarters location
Fremont, CA, US
Year founded
2007