Entry Level Data and AI Consultant Jobs
New grad data and ai consultant jobs welcome recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship project can matter more than a long resume. Most openings are Technology & Software, Energy, and Education roles across on-site, remote, and hybrid settings, with employers like C Spire, Qualcomm, and Mindlance hiring at this level now.
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INTRODUCTION
We are 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, building 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, Agentic frameworks, and model architectures.
BASIC 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.
SALARY RANGE:
The pay range for this position is $110,000 to $160,000 annually. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
PERKS AND BENEFITS:
- 4 weeks accrued paid time off + 9 paid national holidays per year
- Free onsite gym at our Boston Location
- Tuition Reimbursement
- Low cost and excellent coverage health insurance options that start on Day 1 (medical, dental, vision)
- Robust health and wellness program and fitness reimbursements
- Auto and home insurance discounts
- Matching gift opportunities
- Annual 401(k) Employer Contribution (up to 7.5% of your base salary)
- Various Paid Family leave options including Paid Parental Leave
- Resources to promote Professional Development (LinkedIn Learning and licensure assistance)
- Convenient location directly across from South Station and Pre-Tax Commuter Benefits
About the Company
The Plymouth Rock Company and its affiliated group of companies write and manage over $2.3 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
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Top Industries Hiring
- Technology & Software
- Energy
- Education
- Insurance
- Automotive
Entry Level Data and AI Consultant Jobs: Frequently Asked Questions
How do I get an entry level data and ai consultant job?
Employers hiring at this level look for hands-on proof of work over credentials alone. A portfolio of data projects, a completed internship, or coursework in machine learning, SQL, or business analytics demonstrates readiness. Certifications from Google, Microsoft, or AWS can strengthen an application. Tailoring your resume to show how you translated data into a business recommendation gives you a concrete edge over candidates who list tools without context.
Which companies hire entry level data and ai consultants?
Companies hiring entry level data and ai consultants right now include C Spire, Qualcomm, and Mindlance, based on current listings on Migrate Mate as of November 2026. At this level, consulting firms, technology companies, and enterprises building out AI teams tend to post the most openings for candidates early in their careers.
Are there remote entry level data and ai consultant jobs?
Yes, though availability varies by employer and project type. About 17% of entry level data and ai consultant openings are remote or hybrid as of November 2026, giving new graduates flexibility in where they start their careers. On-site roles remain common at consulting firms where client collaboration and in-person training are part of how junior staff develop.
Are these new grad data and ai consultant jobs?
Yes, these listings include new grad, recent graduate, and junior roles. A new grad friendly posting typically welcomes zero to two years of experience, accepts internship or academic project work in place of full-time history, and does not require prior client-facing consulting experience. Look for language like 'recent graduates encouraged' or 'entry level considered' to confirm a role is accessible at this stage.
Which industries hire the most entry level data and ai consultants?
Entry Level data and ai consultant roles concentrate in Technology & Software, Energy, and Education, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they are actively building data infrastructure and AI capabilities, creating consistent demand for junior talent who can support analysis, model development, and client-facing reporting work.