Mid Level AI Application Engineer Jobs
Mid level ai application engineer jobs go to engineers ready to own features end to end, mentor junior teammates, and drive design decisions with limited oversight. Hiring runs across Technology & Software, Education, and Science & Research, with a mix of on-site, remote, and hybrid openings, and employers like BRAIN, JPMorganChase, and NVIDIA competing for engineers at this level now.
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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.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or related field.
- 5+ 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 $135,000 to $200,000 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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Mid Level AI Application Engineer Jobs: Frequently Asked Questions
How do I get a mid level ai application engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you drove decisions, debugged complex failures independently, or improved a system's performance in a measurable way. Tailor your resume to show progression from task execution to feature ownership. Demonstrated fluency with model integration, API design, and production deployment will differentiate your application from candidates still building foundational skills.
Which companies hire mid level ai application engineers?
Companies hiring mid level ai application engineers right now include BRAIN, JPMorganChase, and NVIDIA, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of employers, including large technology firms, enterprise software companies, and growth-stage startups scaling their AI capabilities.
Are there remote mid level ai application engineer jobs?
Yes, remote and hybrid options are common at this level. About 33% of mid level ai application engineer openings are remote or hybrid as of November 2026, reflecting broad employer comfort with distributed AI engineering teams. On-site roles do exist, particularly at companies prioritizing close collaboration on research-adjacent or regulated AI work.
How do I move up to a mid level ai application engineer role?
Moving from entry level to mid level takes deliberate depth-building over time. Focus on owning a full feature or integration from design through production, not just completing assigned tickets. Develop fluency in model deployment, latency optimization, and evaluation frameworks. Seek out projects where you can demonstrate independent judgment, mentor newer teammates, and show measurable impact on the product or system.
Which industries hire the most mid level ai application engineers?
Mid Level ai application engineer roles concentrate in Technology & Software, Education, and Science & Research, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they are actively embedding AI into core products and workflows, creating sustained demand for engineers who can build, integrate, and maintain AI-powered features in production environments.