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Retrieval Augmented Generation Jobs in Massachusetts

Senior Principal AI Engineer

Boston, MA ยท 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 ...

You'll provide technical leadership while driving the development of enterprise-scale AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, NLP ...

AI Solutions Architect (Remote)

Boston, MA ยท On-site +1

$68.50 - $90.25/hr

Design and implement solutions using foundation models, large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI frameworks * Define approaches for model selection ...

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 ...

Senior Principal AI Engineer

Boston, MA ยท 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 ...

Data Engineer

North Reading, MA ยท On-site

$117K - $140K/yr

Preferred : โ€ข Familiarity with Retrieval Augmented Generation (RAG) data structures and experience building semantic layers for LLM or AI agent consumption. Company : BRUNT Workwear is a consumer ...

Principal Engineer, AI Authoring

Boston, MA ยท 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 ...

Lead AI Engineer

Quincy, MA ยท On-site +1

$180K - $280K/yr

Retrieval-Augmented Generation (RAG) and ColBERTv2 pipelines for parsing, indexing, and querying enterprise documents to facilitate answers related to process guidelines, product knowledge, and ...

Lead AI Engineer

Quincy, MA ยท On-site

$180K - $280K/yr

Retrieval-Augmented Generation (RAG) and ColBERTv2 pipelines for parsing, indexing, and querying enterprise documents to facilitate answers related to process guidelines, product knowledge, and ...

Optimize LLM API interactions using prompt engineering, retrieval-augmented generation (RAG), contex management, and performance tuning. * Code Quality / Code Reviews: Write clean, maintainable, 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 are the most commonly searched types of Retrieval Augmented Generation jobs in Massachusetts? The most popular types of Retrieval Augmented Generation jobs in Massachusetts are:
What are popular job titles related to Retrieval Augmented Generation jobs in Massachusetts? For Retrieval Augmented Generation jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Massachusetts look for? The top searched job categories for Retrieval Augmented Generation jobs in Massachusetts are:
What cities in Massachusetts are hiring for Retrieval Augmented Generation jobs? Cities in Massachusetts with the most Retrieval Augmented Generation job openings:
Infographic showing various Retrieval Augmented Generation job openings in Massachusetts 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.

Other

Posted 7 days ago


Job description


Join a cutting-edge AI Platform team as a Lead Data Scientist in a 6-month remote contract-to-hire opportunity. You'll provide technical leadership while driving the development of enterprise-scale AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, NLP, machine learning, and distributed AI architectures to support complex research, document intelligence, and workflow automation systems.
This is a highly visible opportunity for someone who wants to shape the future of enterprise AI. You'll help define AI strategy, lead the design of next-generation intelligent systems, and partner across engineering, product, and business teams to bring advanced AI capabilities into production.
Contract Duration: 6 Months (Contract-to-Hire)
Required Skills & Experience
Bachelor's degree required; Master's degree preferred
8+ years of experience in Data Science, Machine Learning, Applied AI, or related fields
Strong experience with Large Language Models (LLMs) and Generative AI applications
Hands-on experience designing and deploying Retrieval-Augmented Generation (RAG) systems
Expertise in machine learning, NLP, and information retrieval techniques
Experience building and deploying production AI/ML systems at scale
Strong Python programming skills
Experience working with distributed systems and cloud-based AI environments
Deep understanding of agentic AI architectures and autonomous workflows
Proven ability to lead technical initiatives and influence AI strategy
Excellent communication, stakeholder management, and problem-solving skills
Desired Skills & Experience
Experience leading enterprise-scale AI platform initiatives
Familiarity with vector databases and semantic search technologies
Knowledge of legal, regulatory, or document-intensive data environments
Experience with model evaluation, monitoring, governance, and optimization
Exposure to workflow automation and intelligent agent frameworks
Experience mentoring Data Scientists and Machine Learning Engineers
Advanced degree in Data Science, Computer Science, Machine Learning, or a related field
What You Will Be Doing
Tech Breakdown
40% LLMs, RAG, and Generative AI
25% Machine Learning & NLP
20% Agentic AI & Intelligent Automation
15% Technical Leadership & AI Strategy
Daily Responsibilities
65% Hands On
15% Leadership & Mentorship
20% Team Collaboration
You'll lead the design and deployment of advanced AI systems, establish best practices for AI development, mentor team members, collaborate with leadership on AI strategy, and drive the adoption of LLMs, RAG, and agentic AI technologies across enterprise-scale platforms.