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Remote Rag Jobs in Red Oak, TX (NOW HIRING)

Senior Backend Engineer - AI Platform

Dallas, TX · On-site +1

$121K - $159K/yr

This is a remote position; however, the candidate must reside within 30 miles of one of the ... Design solutions for context management, memory, and retrieval-augmented generation (RAG) to ...

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... RAG * Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands ...

Build multi-agent AI systems, workflows, and Retrieval-Augmented Generation (RAG) architectures to ... While many positions offer remote or hybrid work options, these arrangements are subject to change ...

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... RAG * Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands ...

Build multi-agent AI systems, workflows, and Retrieval-Augmented Generation (RAG) architectures to ... While many positions offer remote or hybrid work options, these arrangements are subject to change ...

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How much do remote rag jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for remote rag in Red Oak, TX is $21.29, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $22.60 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Rag, and why are they important?

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What is a Remote RAG (Retrieval-Augmented Generation) specialist?

A Remote RAG specialist is a professional who works with Retrieval-Augmented Generation (RAG) systems, typically in the field of artificial intelligence and machine learning. RAG combines traditional information retrieval techniques with generative models like large language models to provide more accurate and contextually relevant answers to user queries. Remote RAG specialists often build, fine-tune, and maintain these systems while working from a remote location. They may also work on integrating RAG models into applications, improving retrieval accuracy, and customizing outputs based on user needs.

What are some common challenges faced by professionals working in a remote RAG (Responsible AI Governance) role?

Professionals in remote RAG roles often encounter challenges related to cross-functional collaboration and maintaining clear communication, especially when working across different time zones. Ensuring alignment on ethical AI standards and compliance requirements can be complex, as it typically involves coordinating with data scientists, legal teams, and business stakeholders. Staying current with evolving regulatory frameworks and best practices in AI governance is also essential, demanding continuous learning and adaptability. Building trust and rapport within a remote team can require extra effort, but leveraging digital collaboration tools and regular check-ins can help mitigate these challenges.
What job categories do people searching Remote Rag jobs in Red Oak, TX look for? The top searched job categories for Remote Rag jobs in Red Oak, TX are:
What cities near Red Oak, TX are hiring for Remote Rag jobs? Cities near Red Oak, TX with the most Remote Rag job openings:
Senior Backend Engineer - AI Platform

Senior Backend Engineer - AI Platform

WEX

Dallas, TX • On-site, Remote

$121K - $159K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


WEX Inc. rating

8.1

Company rating: 8.1 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

8th of 18 rated payment service providers


Job description

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Boston, MA; San Francisco Bay Area, CA; Dallas, TX; Salt Lake City, UT; Seattle, WA; and Portland, ME

About the Team/Role


We are seeking a seasoned Sr. Software Engineer in the North America Mobility organization. This role will sit in the Platform team that focuses on building AI Platform to support the feature development team to build robust features faster. You will contribute to the architecting and realization of our next-generation Agentic AI Platform. Within this capacity, you will be responsible for the design, development, and deployment of autonomous AI agents, skills, MCP servers, AI tools engineered for advanced reasoning, strategic planning, and the orchestration of intricate financial and operational workflows. Operating at the vanguard of generative AI, distributed systems, and fintech, you will empower WEX to deliver highly intelligent, proactive solutions to an expansive global user base.

Our Platform team is dedicated to architecting scalable, robust, and maintainable UI and API platform solutions that empower internal feature development teams to build at velocity. Within the NAM Mobility ecosystem, our products facilitate strategic credit issuance to fleet organizations and their workforce through WEX-branded or co-branded credit instruments, accepted across a vast network of fueling stations and merchant partners. We provide fleet managers and operators with advanced spend orchestration capabilities, encompassing fuel discounts and sophisticated spend controls that permit precise configuration of merchant restrictions, transaction limits, and velocity thresholds to optimize operational efficiency.


How you'll make an impact:

  • Design, develop, and maintain robust, scalable, and high-performance object oriented code in our backend services.
  • Develop public REST APIs using Java and internal gRPC APIs for inter-service and inter-system communication.
  • Craft systems designs, lead design decisions, and drive alignment with other senior engineers.
  • Write automated unit tests, integration tests, end-to-end tests, concurrency tests, load/performance tests.
  • Analyze existing systems to identify bottlenecks, tech debt, and implement scalability, and stability improvements.
  • Implement automation for testing, monitoring, healing, and scaling applications, continuous integration and deployment to reduce time to market.
  • Collaborate with cross-functional teams, including product managers, designers, and other engineers, to define and implement new features.
  • Conduct code reviews (comment, approve, seek revisions, merge), mentor junior and mid-level engineers, and actively promote engineering best practices.
  • Dive deep and troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure lasting performance and reliability.
  • Conduct objective and comparative analyses of competing technologies to advise the team of pros and cons of a technology solution.
  • Maintain robust documentation (design docs, run books, change management docs, and readiness plans).
  • Provide live-site support for production applications by monitoring systems, ensuring rapid incident resolution, and driving continuous improvement.
  • Drive cross-team projects as a single-threaded-owner (STO) or tech lead, and actively unblock other engineers to make progress.

Agentic AI & Intelligent Systems :

  • Design and build agentic AI systems and services, enabling autonomous workflows, reasoning, and task execution within Mobility platforms.
  • Develop AI agents from scratch, including orchestration, tool usage, memory, and multi-step decision-making capabilities.
  • Implement and scale multi-agent architectures to support complex, distributed use cases across payments and fleet ecosystems.
  • Integrate systems using Model Context Protocol (MCP) or similar frameworks to enable secure and scalable interaction between AI agents, APIs, and enterprise data sources.
  • Build and optimize LLM-powered services (e.g., OpenAI APIs, LangChain) for production-grade performance, reliability, and cost efficiency.
  • Implement evaluation frameworks, observability, and guardrails to ensure correctness, safety, and compliance of AI-driven systems.
  • Design solutions for context management, memory, and retrieval-augmented generation (RAG) to enhance agent effectiveness.

Experience you'll bring:

  • Bachelor's degree in Computer Science or Software Engineering
  • 5-8 years of professional experience in software engineering
  • Strong understanding of data structures and algorithms, object-oriented design, and problem-solving skills
  • Expertise in designing and developing internet-scale services with scalability, availability, security, and reliability design tenets
  • Excellent written and verbal communication skills, and a collaborative and empathetic mindset
  • Proficiency in backend development, with expertise in Java or C#, frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL


Agentic AI & MCP Experience:

  • Hands-on experience building or contributing to AI/LLM-powered applications or agent-based systems
  • Familiarity with agent frameworks, tool-use patterns, and orchestration of LLM workflows
  • Experience integrating AI systems with external tools/APIs using MCP or similar protocols
  • Understanding of prompt engineering, embeddings, and vector-based retrieval systems
  • Experience designing systems for scaling AI workloads in production environments

Preferred Qualifications

  • Master's degree in computer science or software engineering
  • 8+ years of experience in software engineering
  • Experience with Python, Java, event-driven architecture and tools like Kafka
  • Experience working on card payments
  • Familiarity with cloud-native architecture (containerization using tools such as Docker and Kubernetes)
  • Awareness of API security and PCI DSS compliance requirements
  • Ability to work on existing codebase, contribute improvements, and adapt to legacy systems' constraints
  • Nice to Have (AI Focus):
  • Experience building AI skills & deploying AI solutions to production environments
  • Experience building production-grade AI agents or copilots
  • Familiarity with multi-agent systems and distributed AI architectures
  • Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)
  • Knowledge of AI evaluation techniques, safety practices, and responsible AI principles

Nice to Have (AI Focus):

  • Experience building AI skills & deploying AI solutions to production environments
  • Experience building production-grade AI agents or copilots
  • Familiarity with multi-agent systems and distributed AI architectures
  • Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)
  • Knowledge of AI evaluation techniques, safety practices, and responsible AI principles
The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $121,500.00 - $145,500.00

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