Entry Level AI Product Engineer Jobs
New grad ai product engineer jobs open doors for recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship work can matter more than a long resume. Most openings mix on-site, remote, and hybrid settings across Technology & Software, Marketing & Advertising, and Energy, with employers like TikTok, JPMorganChase, and Angi 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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Entry Level AI Product Engineer Jobs: Frequently Asked Questions
How do I get an entry level ai product engineer job?
Employers hiring at the entry level look for candidates who can demonstrate hands-on work with AI tools, APIs, or product prototypes, so a GitHub portfolio or a capstone project often carries more weight than years of experience. Familiarity with product thinking, basic machine learning concepts, and cross-functional communication gives candidates a real edge. Targeting companies with dedicated AI product teams and applying to roles that explicitly welcome new graduates sharpens your chances further.
Which companies hire entry level ai product engineers?
Companies hiring entry level ai product engineers right now include TikTok, JPMorganChase, and Angi, based on current listings on Migrate Mate as of November 2026. The mix tends to include fast-growing AI startups, established technology firms building out product teams, and enterprise organizations launching AI-driven features who are willing to develop junior talent from the ground up.
Are there remote entry level ai product engineer jobs?
Yes, though availability varies by employer and team structure. About 17% of entry level ai product engineer openings are remote or hybrid as of November 2026, reflecting how many AI product teams have adopted flexible work models. On-site roles remain common at early-stage startups where in-person collaboration is central to product development, so checking each listing's work setting before applying is worthwhile.
Are these new grad ai product engineer jobs?
Yes, the openings on this page include new grad, recent graduate, and junior ai product engineer roles alongside other entry level listings. A new grad-friendly posting typically welcomes zero to two years of experience, counts internships or co-ops toward requirements, and accepts a portfolio of personal or academic projects in place of professional history. If a job description uses terms like "junior," "associate," or "entry level," it is generally open to new grad applicants.
Which industries hire the most entry level ai product engineers?
Entry Level ai product engineer roles concentrate in Technology & Software, Marketing & Advertising, and Energy, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at the junior level because they are actively integrating AI into their core products and need candidates who can bridge technical implementation and product decision-making, even without an extensive professional background.