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Remote Retrieval Augmented Generation Jobs in Pepperell, MA

Motorola

Senior AI Engineer (US Remote)

Waltham, MA · Remote

$180K - $210K/yr

RAG (Retrieval-Augmented Generation) architectures * Agentic frameworks (LangChain, LlamaIndex, or ... REMOTE Basic Requirements * 8+ years experience in software development * AND 2+ years with AI ...

UKG, Inc.

Lead Software Development Engineer

Lowell, MA · On-site +1

Experience with retrieval-augmented generation, vector search, AI evaluation, or multi-agent systems. * Experience modernizing manual testing processes and replacing tool-specific automation with ...

UKG, Inc.

Software Development Engineer

Lowell, MA · On-site +1

Familiarity with retrieval-augmented generation, vector search, AI evaluation, and multi-agent systems. * Experience with observability platforms such as OpenTelemetry, Azure Monitor, Application ...

All JobsRetrieval Augmented Generation JobsRemote Retrieval Augmented Generation JobsRemote Retrieval Augmented Generation Jobs in Pepperell, MA

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 cities near Pepperell, MA are hiring for Remote Retrieval Augmented Generation jobs?

Cities near Pepperell, MA with the most Remote Retrieval Augmented Generation job openings:

Remote Retrieval Augmented Generation jobs near you
Infographic showing various Remote Retrieval Augmented Generation job openings in Pepperell, MA as of June 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 100% Remote job distribution.

Full Stack AI Engineer

BIRDSVUE LLC

Dunstable, MA • Remote

$60 - $70/hr

Full-time

Retirement

Re-posted 9 days ago

Job description

Benefits:
  • 401(k)
  • Competitive salary

Full Stack AI EngineerIntroduction: We are seeking a highly motivated Full Stack AI Engineer who can design, build, and scale production-grade AI applications from concept to deployment. You will work directly with product leadership and customers to create intelligent systems leveraging LLMs, AI agents, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and modern cloud-native architectures.
Responsibilities:
AI & Agentic Systems
  • Design and develop AI-powered applications using OpenAI, Azure OpenAI, Anthropic, Gemini, and open-source models.
  • Build multi-agent and agentic workflows using LangGraph, LangChain, Semantic Kernel, CrewAI, or equivalent frameworks.
  • Develop Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, document indexing, and knowledge retrieval systems.
  • Integrate AI models with enterprise systems, APIs, SaaS platforms, and business workflows.
  • Design prompt orchestration, evaluation frameworks, guardrails, observability, and AI governance controls.
Full Stack Development
  • Build scalable frontend applications using React, Next.js, TypeScript, and modern UI frameworks.
  • Develop backend services, APIs, microservices, and event-driven architectures using Python (FastAPI), Node.js, or .NET.
  • Design and optimize SQL and NoSQL databases.
  • Implement authentication, authorization, and secure enterprise-grade integrations.
  • Create reusable APIs and SDKs for AI capabilities across multiple products.
Cloud & Platform Engineering
  • Deploy AI applications on Azure, AWS, or Google Cloud Platform.
  • Build containerized services using Docker and Kubernetes.
  • Implement CI/CD pipelines, infrastructure-as-code, monitoring, and observability.
  • Optimize AI infrastructure for scalability, performance, and cost efficiency.
Product & Innovation
  • Partner with product managers and customers to translate business challenges into AI solutions.
  • Rapidly prototype and productionize AI use cases.
  • Evaluate emerging AI technologies and recommend adoption strategies.
  • Contribute to AI platform roadmap and innovation initiatives.
Requirements:
Required Qualifications:
  • Bachelor''s degree in Computer Science, Engineering, or related field.
  • 5+ years of full-stack software development experience.
  • Strong proficiency in: 
    • Python
    • TypeScript / JavaScript
    • React / Next.js
    • Node.js or FastAPI
  • Experience building REST APIs and microservices.
  • Hands-on experience with: 
    • OpenAI / Azure OpenAI APIs
    • RAG architectures
    • Vector databases (Pinecone, Weaviate, FAISS, Chroma, Azure AI Search)
    • LangChain, LangGraph, Semantic Kernel, or similar frameworks
  • Experience with Docker, Kubernetes, and cloud-native architectures.
  • Strong understanding of software engineering best practices, testing, CI/CD, and Agile development.

This is a remote position.