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Retrieval Augmented Generation Jobs in Woonsocket, RI

Nastech Global

GCP Gen AI Architect

Boston, MA · On-site

Build Retrieval-Augmented Generation (RAG) pipelines to improve the quality of AI-generated responses. Collaborate with various stakeholders to integrate and deploy AI models into production ...

Vrtx

Principal Engineer, AI Authoring

Boston, MA · Hybrid

$166K - $250K/yr

Build and optimize sophisticated Retrieval-Augmented Generation (RAG) systems that accurately pull from vast clinical and regulatory data sources to assist in document creation. * Engineer the data ...

Vrtx

Senior Principal AI Engineer

Boston, MA · On-site

$136K - $187K/yr

This role will lead the design and implementation of scalable, secure, and reusable capabilities for agentic AI, with a strong focus on retrieval-augmented generation (RAG), orchestration frameworks ...

Vertex Pharmaceuticals

Senior Principal AI Engineer

Boston, MA · On-site

$136K - $187K/yr

This role will lead the design and implementation of scalable, secure, and reusable capabilities for agentic AI, with a strong focus on retrieval-augmented generation (RAG), orchestration frameworks ...

apiphani

Senior Software Engineer (AI / LLMs)

Boston, MA · Remote

$120K - $160K/yr

You'll work on distributed systems that combine traditional infrastructure automation with large language models (LLMs), retrieval-augmented generation (RAG), and intelligent agents. What You'll Do

Deloitte

Oracle Gen AI Manager

Boston, MA

Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...

Winaxis

AI/ML Engineer

Boston, MA · On-site

$124K - $149K/yr

LangChain LlamaIndex Hugging Face OpenAI APIs Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS) Experience in RAG (Retrieval-Augmented Generation) implementations. Knowledge of MLOps tools and ...

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Retrieval Augmented Generation information

What does a retrieval augmented generation engineer do?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What is a retrieval augmented generation?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What skills and qualifications are needed for retrieval augmented generation?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

What job categories do people searching Retrieval Augmented Generation jobs in Woonsocket, RI look for? The top searched job categories for Retrieval Augmented Generation jobs in Woonsocket, RI are:
What cities near Woonsocket, RI are hiring for Retrieval Augmented Generation jobs? Cities near Woonsocket, RI with the most Retrieval Augmented Generation job openings:
Retrieval Augmented Generation jobs near you
Infographic showing various Retrieval Augmented Generation job openings in Woonsocket, RI as of August 2026, with employment types broken down into 66% Full Time, 31% Part Time, and 3% Contract. Highlights an 69% Physical, 2% Hybrid, and 29% Remote job distribution.

Senior AI Engineer - Boston, MA - Contract Opportunity

Zodiac Solutions

Boston, MA • On-site

$113K - $155K/yr

Contractor

Re-posted 2 days ago

Job description

Job Title: Senior AI Engineer
Location: Boston, MA – 4 days/week onsite

Duration: Contract Opportunity

Senior Level – 15+ yrs Only

F2F Interview is required for final round mandatory.

Job Description:

This role focuses on developing AI applications powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP) servers, and Agentic AI across the enterprise. Need someone with Langchain/LangGraph exp.

Seeking a highly skilled AI Engineer to design and build Generative and Agentic AI systems that transform how our company operates and serves customers. This role focuses on developing AI applications powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP) servers, and Agentic AI across the enterprise for internal and customer facing use cases.

The ideal candidate has strong experience with a modern AI/ML stack, including a profound Python experience, including AI relevant packages and tools, LLM architectures and frameworks, RAG, MCP, prompt engineering, use of AI tools, budling teams of AI agents, and production-grade AI systems design and development.

You will work closely with technology, data, and business teams to build scalable AI solutions that drive operational efficiency and innovation across the enterprise.

Key Responsibilities:

  • Design, build, and deploy scalable LLM-powered applications, solutions, and digital products for customer support, business use cases, and internal productivity.
  • Develop AI agents, Agentic Platforms, and Agentic AI systems capable of reasoning, planning, and executing multi-step workflows.
  • Implement Retrieval-Augmented Generation (RAG) architectures and pipelines to leverage proprietary data, and internal knowledge bases.
  • Build MCP servers, multi-connectivity enabled and multi-modal Agentic platforms, and AI assistants to support internal teams and customer facing.
  • Integrate AI/ML solutions with enterprise systems, APIs, and data platforms.
  • Design prompt strategies, evaluation frameworks, and guardrails to ensure accuracy, security, and regulatory compliance.
  • Optimize LLM performance through fine-tuning, prompt engineering, and model orchestration.
  • Develop MLOps and LLMOps pipelines for monitoring, evaluation, and continuous improvement of AI systems.
  • Help in forming buy or build decisions and work with external vendors, consultants and internal teams to deliver scalable top-quality AI solutions timely.
  • Stay up to date with emerging advancements in AI/ML, Generative AI, Agentinc frameworks, and model architectures. 

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related field.
  • 2+ years of software engineering experience, including work with machine learning (ML) or AI systems.
  • Hands-on experience building LLM-powered applications in production environments.
  • Strong programming skills in Python, and familiarity with AI/ML relevant packages such as NumPy, Pandas, SciPy and Scikit-learn.
  • Experience with LLM ecosystems such as:
    • OpenAI / Anthropic / Google, Open-source LLMs
    • Hugging Face
    • LangChain, LlamaIndex, or similar orchestration frameworks
  • Experience building RAG pipelines and working with vector databases.
  • Understanding of prompt engineering, embeddings, and model evaluation.
  • Experience building APIs, MCPs, and scalable backend services.
  • Experience with Claude Code, Codex, Cursor, GitHub Copilot, or similar.
  • Ability to collaborate with cross-functional teams.
  • Passion for technology and AI.

Preferred Qualifications:

  • Experience building AI agents, agentic platforms, or autonomous workflows.
  • Familiarity with agent frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, Frontier, etc.).
  • Experience with fine-tuning LLMs or parameter-efficient training methods (LoRA, PEFT).
  • Experience with cloud-based AI infrastructure (AWS, Azure, or GCP).
  • Familiarity with Java, JS, and Java applications and environments.
  • Experience with MLOps / LLMOps tools and evaluation pipelines.

Experience implementing AI governance, observability, and guardrails.