2

Remote Retrieval Augmented Generation Jobs in Dallas, TX

Lead AI Engineer- Remote

Richardson, TX · On-site +1

$93K - $122K/yr

Build retrieval augmented generation (RAG) and hybrid search pipelines to power robust question answering over clinical and operational data * Design, code, test, document, and maintain high quality ...

... RAG (Retrieval Augmented Generation) architectures, agentic design, A2A (Agent to Agent) orchestration, MCP (Model Context Protocol) - based ecosystems, AI assisted generation of application ...

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 ...

Lead Engineer

Dallas, TX · Remote

$104K - $138K/yr

Contract-to-Hire - 3 months, Remote Pay: 60-65/HR Benefits: This position is eligible for medical ... Evaluate and apply embedding models, vector similarity search, and retrieval-augmented generation ...

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 ...

Global Services & Delivery Location: [Remote / Hybrid - specify] Reports to: Head of Customer ... Experience with LLM and agent frameworks, retrieval-augmented generation, or workflow automation.

... Retrieval-Augmented Generation (RAG) patterns, evaluation, and governance capabilities. Success in this role is measured by the adoption of architectural standards, the reliability and scalability of ...

New

Showing results 21-40

Remote Retrieval Augmented Generation information

What is remote retrieval augmented generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.

What skills and qualifications are needed to thrive as a remote retrieval augmented generation engineer?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What are common challenges faced by professionals working in remote retrieval augmented generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

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

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Dallas, TX?

The most popular types of Retrieval Augmented Generation jobs in Dallas, TX are:

What are popular job titles related to Remote Retrieval Augmented Generation jobs in Dallas, TX?

For Remote Retrieval Augmented Generation jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Remote Retrieval Augmented Generation jobs in Dallas, TX look for?

The top searched job categories for Remote Retrieval Augmented Generation jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Remote Retrieval Augmented Generation jobs?

Cities near Dallas, TX with the most Remote Retrieval Augmented Generation job openings:

Lead AI Engineer- Remote

UnitedHealth Group

Richardson, TX • On-site, Remote

$93K - $122K/yr

Full-time

Retirement

Re-posted yesterday


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

192nd of 898 rated healthcare providers


Job description

OptumInsightis improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, andultimately consumers. Our deepexpertisein the industry and innovative technology empower us to help organizations reduce costs while improving risk management,qualityand revenue growth. Ready to help us deliver results that improve lives?Join us to startCaring. Connecting. Growing together.


We are seeking a Lead Software Engineer to design, build, and scale next-generation agentic AI systems and advanced solutions that improve healthcare delivery and operations.


In this individual contributor (IC) leadership role, you will operate as a hands-on technical expert, driving architecture, development, and deployment of complex AI-powered solutions. You will architect end-to-end question answering and multiagent workflows, integrate with our internal AI platform (e.g., UAIS), and ensure responsible, compliant use of AI in a regulated environment (HIPAA). The ideal candidate combines deep software engineering expertise with hands-on experience in LLMs, RAG, agent/tool use, and evaluation on modern cloud and data platforms.  


This role is ideal for someone who thrives on solving complex problems, enjoys working at the intersection of AI/ML and distributed systems, and wants to make a meaningful impact in a highly regulated, mission-driven environment.


You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.


Primary Responsibilities:

  • Agentic AI Architecture & Delivery 
    • Design and implement (multi) agentic workflows where LLMs plan, decompose tasks, invoke tools/APIs, and synthesize answers across heterogeneous data sources and services
    • Build retrieval augmented generation (RAG) and hybrid search pipelines to power robust question answering over clinical and operational data
    • Design, code, test, document, and maintain high quality, scalable Big Data and cloud solutions
    • Develop scalable microservices and APIs for integrating agent capabilities into clinician tools and internal apps
    • Create prototypes/POCs and conduct design/code reviews to derisk delivery and raise engineering quality
  • LLMs, GenAI & Model Adaptation 
    • Leverage and adapt LLMs; perform prompt engineering, grounding, guard railing, and domain adaptation for healthcare terminology and tasks
    • Design intelligent frameworks and finetune models for compliance, accuracy, and ethical standards
    • Establish evaluation frameworks (automatic human in the loop) to measure faithfulness, helpfulness, bias, toxicity, privacy leakage, and overall quality
  • Data & Platform Engineering 
    • Partner with data engineering to build feature/retrieval stores, embeddings pipelines, and ETL/ELT jobs on Spark/Databricks; design analytics models and rules engines
    • Define and develop APIs for integrations across the enterprise; improve data access patterns for low latency inference
  • Delivery, MLOps & Reliability 
    • Own MLOps/LLMOps: CI/CD for models/prompts, automated tests (unit/contract/eval), versioning, lineage, rollback; enable blue/green or canary releases
    • Instrument SLOs/SLIs (latency, availability, hallucination/defect rate) and cost KPIs (tokens, GPU hours) with dashboards and alerts
    • Lead production deployments on internal platforms (e.g., UAIS) with solid observability, reliability, and cost controls
  • Security, Privacy & Compliance 
    • Champion HIPAA and regulated industry controls; integrate access controls, PHI/PPI safeguards, data minimization, encryption, and auditability
    • Collaborate with legal, compliance, and clinical safety to operationalize Responsible AI principles
  • Product, Estimation & Collaboration 
    • Analyze and define customer requirements; assist in defining product technical architecture and delivery roadmaps
    • Provide effort estimates and inputs for resource planning; collaborate with QA, architecture, and peer teams
    • Write technical documentation, support production, and mentor engineers, and keep skills current through continuous learning


You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

  • Bachelor's degree in Engineering, Computer Science, IT, or related fields
  • 10 years of total technology experience 
  • 8 years hands on software development/data engineering/analytics with solid AI/ML delivery (Azure preferred) with Scala, Python, PySpark
  • 4 years hands on with Databricks
  • 4 years with ADF/Airflow (orchestration/scaling)
  • 4 years with big data & streaming (Hadoop, MapReduce/HDFS, Spark, Kafka); Docker/Kubernetes
  • 4 years with MySQL and NoSQL databases
  • 4 years with Agile/Scrum, GitHub, Jenkins CI/CD, JUnit; solid coding standards and code reviews
  • 2 years with LLMs & GenAI (Langchain, LangGraph, RAG, Vector DB, Azure Open AI, MCP Server, Agents, LangFuse)
  • 2 years of experience with container (Docker/Kubernetes) 
  • 1 years with Proficiency building services or full stack apps (e.g., FastAPI/Flask, Node.js, React/Angular, TypeScript, HTML/CSS)


Preferred Qualifications:

  • Healthcare experience; familiarity with clinical datasets
  • Experience working in regulated industries, with knowledge of ethical AI/ML practices and compliance requirements
  • SOA and enterprise integration concepts
  • Publications/patents or notable open-source contributions
  • Proven excellent analysis, problem solving, and communication skills


*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy


Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $112,700 - $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.


Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.


At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.


UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.


What UnitedHealth Group employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom