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Generative Ai Engineer Jobs in Massachusetts (NOW HIRING)

AI Engineer

Wakefield, MA ยท On-site

$110K - $150K/yr

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

AI Engineer

Wakefield, MA ยท On-site

$110K - $150K/yr

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

Experience with Generative AI Large Language Models (LLMs), including solution development and fine-tuning for domain-specific tasks. * Proficiency in at least one programming language such as Python ...

Senior Agentic AI Engineer (Python)_

Boston, MA ยท On-site

$132K - $177K/yr

Senior Agentic AI Engineer (Python) Experience: 5 10 years Location: Onsite / Offshore (Flexible ... The role focuses on Generative AI, LLMs, agentic workflows, RAG architectures, AI orchestration ...

Senior Agentic AI Engineer (Python)

Boston, MA ยท On-site

$132K - $177K/yr

Hello Senior Agentic AI Engineer (Python) Experience: 5 10 years Location: Boston, MA Primary ... The role focuses on Generative AI, LLMs, agentic workflows, RAG architectures, AI orchestration ...

New

Senior Agentic AI Engineer (Python)

Boston, MA ยท On-site

$132K - $177K/yr

Senior Agentic AI Engineer (Python) Boston, MA - Onsite Primary Objective We are seeking a Senior ... The role focuses on Generative AI, LLMs, agentic workflows, RAG architectures, AI orchestration ...

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Showing results 1-20

Generative Ai Engineer information

See Massachusetts salary details

$41.5K

$126.5K

$209.1K

How much do generative ai engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for generative ai engineer in Massachusetts is $126,538.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,600.00 and $165,500.00 per year, depending on experience, location, and employer.

What is a generative AI engineer?

A Generative AI Engineer is a specialized software engineer who designs, develops, and optimizes AI models that generate content such as text, images, audio, or video. They work with deep learning frameworks, train large-scale models, and fine-tune pre-trained architectures to improve performance. Their role involves data preprocessing, model deployment, and continuous optimization to enhance AI-generated outputs. Generative AI Engineers typically collaborate with data scientists, researchers, and product teams to integrate AI solutions into applications and services.

What does a generative AI engineer do?

As a Generative AI Engineer, your typical responsibilities involve designing, developing, and optimizing generative models for tasks such as image synthesis, natural language generation, or data augmentation. You will often collaborate closely with data scientists, researchers, and product teams to translate business or research goals into scalable AI solutions. Day-to-day work may include experimenting with different neural network architectures, optimizing model performance, and deploying models to production environments. Many roles also offer opportunities to contribute to publications or open-source projects, and there is strong potential for career growth into lead engineering or research positions as you gain experience.

What are the key skills and qualifications needed to thrive as a generative AI engineer?

To thrive as a Generative AI Engineer, you need a deep understanding of machine learning, deep learning architectures (such as GANs and transformers), and proficiency in programming languages like Python, along with a degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and relevant cloud platforms, as well as certifications in AI or ML, are highly valuable. Strong problem-solving skills, creativity, and effective communication help engineers collaborate and innovate within diverse, multidisciplinary teams. These skills are critical for developing advanced AI models, driving continuous improvement, and successfully translating complex research into practical applications.

How do I become a generative AI engineer?

To become a generative AI engineer, you should have a strong foundation in programming languages such as Python, experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of deep learning models such as GANs or transformers. Gaining expertise through relevant coursework, online tutorials, and hands-on projects is essential, along with understanding data preprocessing and model evaluation. Building a portfolio of AI projects and staying updated with the latest research can also improve job prospects in this field.

What is the salary of a generative AI engineer?

The salary of a generative AI engineer typically ranges from $100,000 to $180,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in deep learning and machine learning frameworks may earn higher compensation, often including bonuses and stock options.

What are the most commonly searched types of Generative Ai Engineer jobs in Massachusetts?

The most popular types of Generative Ai Engineer jobs in Massachusetts are:

What are popular job titles related to Generative Ai Engineer jobs in Massachusetts?

For Generative Ai Engineer jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Generative Ai Engineer jobs in Massachusetts look for?

The top searched job categories for Generative Ai Engineer jobs in Massachusetts are:

What cities in Massachusetts are hiring for Generative Ai Engineer jobs?

Cities in Massachusetts with the most Generative Ai Engineer job openings:

Infographic showing various Generative Ai Engineer job openings in Massachusetts as of August 2026, with employment types broken down into 6% Internship, 82% Full Time, 6% Part Time, and 6% Contract. Highlights an 77% In-person, 6% Hybrid, and 17% Remote job distribution, with an average salary of $126,538 per year, or $60.8 per hour.

Agentic AI & Generative AI Engineer

Career Soft Solutions Inc

Boston, MA โ€ข On-site

$105K - $145K/yr

Other

Posted 21 days ago


Job description

Job Title: Agentic AI & Generative AI Engineer
Location: Onsite โ€“ Richardson,TX/
charlotte, NC
Employment Type: Full-Time / Contract

Job Summary

We are seeking an experienced Agentic AI & Generative AI Engineer to design, develop, and deploy next-generation AI applications powered by Large Language Models (LLMs), autonomous AI agents, and modern AI frameworks. The ideal candidate will have hands-on experience building intelligent AI systems using OpenAI, Anthropic, Gemini, Llama, LangChain, LangGraph, CrewAI, AutoGen, and Retrieval-Augmented Generation (RAG) architectures.

This role involves developing AI agents capable of reasoning, planning, tool usage, memory management, and workflow automation while integrating enterprise data sources and cloud infrastructure.


Key Responsibilities

  • Design, build, and deploy Agentic AI solutions capable of autonomous decision-making and multi-step reasoning.
  • Develop Generative AI applications using Large Language Models (LLMs) such as GPT-4/5, Claude, Gemini, and Llama.
  • Build multi-agent systems using frameworks like LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
  • Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge repositories.
  • Develop AI copilots, intelligent assistants, chatbots, and workflow automation solutions.
  • Integrate AI applications with REST APIs, enterprise applications, databases, and cloud services.
  • Fine-tune prompt engineering strategies to improve response quality, reasoning, and accuracy.
  • Design agent memory, planning, orchestration, and tool-calling capabilities.
  • Deploy AI workloads on Azure, AWS, or Google Cloud using containerized architectures.
  • Optimize inference performance, latency, scalability, and cost.
  • Implement AI governance, security, responsible AI, and compliance best practices.
  • Monitor model performance and continuously improve AI systems using user feedback and evaluation metrics.
  • Collaborate with product owners, architects, data scientists, and software engineers throughout the AI development lifecycle.

Required Qualifications

  • Bachelor''''''''s or Master''''''''s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
  • 5+ years of software engineering experience.
  • 2+ years of hands-on experience building Generative AI or LLM-powered applications.
  • Strong programming skills in Python.
  • Experience with OpenAI, Anthropic Claude, Gemini, Llama, or other foundation models.
  • Strong understanding of Prompt Engineering and LLM optimization.
  • Experience building RAG applications.
  • Experience with Vector Databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or Azure AI Search.
  • Experience with LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
  • Knowledge of embeddings, chunking, semantic search, and retrieval optimization.
  • Experience integrating AI solutions with REST APIs and enterprise applications.
  • Strong understanding of Docker, Kubernetes, CI/CD pipelines, and Git.
  • Experience deploying AI solutions on Azure, AWS, or Google Cloud.

Preferred Qualifications

  • Experience fine-tuning open-source LLMs.
  • Knowledge of Model Context Protocol (MCP).
  • Experience with AI agent orchestration platforms.
  • Familiarity with AI observability tools such as LangSmith, Phoenix, Weights & Biases, or MLflow.
  • Experience with Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
  • Knowledge of knowledge graphs and graph databases (Neo4j).
  • Experience implementing Responsible AI and AI governance frameworks.
  • Experience working with structured and unstructured enterprise data.

Technical Skills

Programming

  • Python
  • SQL
  • JavaScript (preferred)

AI/LLMs

  • OpenAI GPT
  • Anthropic Claude
  • Google Gemini
  • Meta Llama
  • Mistral
  • Hugging Face Transformers

Agentic AI Frameworks

  • LangGraph
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • OpenAI Agents SDK

RAG & Retrieval

  • LangChain
  • LlamaIndex
  • Azure AI Search
  • Pinecone
  • Weaviate
  • Chroma
  • FAISS
  • Milvus

Cloud Platforms

  • Microsoft Azure
  • AWS
  • Google Cloud Platform

DevOps

  • Docker
  • Kubernetes
  • GitHub Actions
  • Azure DevOps
  • Jenkins
  • Terraform

Databases

  • PostgreSQL
  • MongoDB
  • Redis
  • Neo4j

APIs & Integration

  • REST APIs
  • GraphQL
  • MCP
  • Webhooks

Observability

  • LangSmith
  • MLflow
  • Weights & Biases
  • OpenTelemetry

Nice-to-Have Skills

  • AI workflow automation
  • Multi-agent orchestration
  • Human-in-the-loop systems
  • Reinforcement learning concepts
  • AI safety and governance
  • Prompt optimization and evaluation
  • Knowledge graph integration
  • AI-powered business process automation

Soft Skills

  • Strong analytical and problem-solving skills.