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Applied AI Engineer

N2P Systems · Nashville, TN, USA · no salary listed · via jobspy:linkedin
75
Open listing

Fit analysis

The candidate is an exceptionally strong full-stack engineer with deep experience in building high-availability, complex data systems and B2B e-commerce platforms. However, the resume lacks direct hands-on evidence of working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or Python/ML frameworks, which are central to this Applied AI role.

Where you fit

  • Strong Programming Fundamentals: Proven expertise in multiple modern languages including JavaScript, TypeScript, React, Next.js, and Node.js, demonstrating the ability to build scalable applications.
  • Complex Data Integration: Experience integrating disparate systems using GraphQL (Hasura) and managing complex data flows with PostgreSQL and live blockchain nodes, which is foundational for RAG implementation.
  • Building Scalable/High-Availability Systems: Engineered real-time SaaS platforms (Colony Watch) monitoring 1,800+ assets and designed infrastructure rollouts ensuring zero disruption, demonstrating robust system design skills.
  • Full-Stack Development Lifecycle: Expertise in architecting and deploying end-to-end solutions, from headless storefronts (Next.js/Shopify) to custom backends (Node.js/Express).
  • API & Microservices Experience: Developed multiple integrations using third-party APIs and managed complex data bridges between systems (e.g., WooCommerce with Hasura), meeting the microservice requirement.
  • Operational Process Optimization: Proven ability to drive measurable business improvements, such as optimizing B2B quote accuracy by 30%, showing an understanding of translating technical work into business value.

Where you may struggle

  • Generative AI/LLM Experience: The resume does not show any direct experience integrating or utilizing Large Language Models (OpenAI, Anthropic) or building applications around them.
  • RAG and Vector Databases: There is no mention of implementing Retrieval-Augmented Generation (RAG) workflows or working with vector databases/semantic search, which are key requirements for the role.
  • Python Proficiency: While proficient in JavaScript/Node.js, Python is the industry standard language for AI/ML development; this gap could slow down initial contribution to an AI team.
  • Cloud AI Services: The experience mentions general infrastructure rollouts but lacks specific hands-on exposure to cloud AI services like AWS Bedrock or Azure OpenAI.
  • Agentic Workflow Frameworks: There is no evidence of working with agentic frameworks such as LangChain or LangGraph, which are preferred qualifications for this role.

Cover letter

Job description
Applied AI Engineer Experience: 3–5 Years Employment Type: Full-Time Work Model: Hybrid – Minimum 3 Days Onsite Per Week The candidates will need to be local to either Nashville, TN or Tampa, FL with hybrid set up (2-3 days on sight). Travel: 0–10% Job Overview We are seeking a motivated and hands-on Applied AI Engineer with 3–5 years of software engineering experience and practical exposure to Generative AI and agentic AI technologies. The ideal candidate will contribute to designing, developing, testing, and deploying scalable software solutions that leverage AI to solve real-world business problems. The candidate should have strong programming fundamentals, experience integrating Large Language Models (LLMs), and exposure to cloud-native application development. This role offers an opportunity to collaborate with cross-functional teams, experiment with emerging AI technologies, and implement AI-enabled engineering practices throughout the software development lifecycle. Key Responsibilities Design, develop, test, and maintain scalable software applications and AI-powered solutions. Integrate LLMs from providers such as OpenAI, Anthropic, or open-source platforms into business applications. Develop and support Generative AI applications using Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases. Build APIs, microservices, and cloud-native applications using modern programming languages and frameworks. Participate in technical design, requirement analysis, code reviews, testing, and production support. Apply AI-assisted development tools for code generation, debugging, testing, code reviews, and documentation. Explore and implement agentic AI workflows using frameworks such as LangChain and LangGraph. Support automated deployments and integrate quality, security, and testing checks into CI/CD pipelines. Collaborate with product managers, designers, and engineering teams to translate business requirements into technical solutions. Follow software engineering best practices for code quality, scalability, security, performance, and maintainability. Participate in rapid prototyping and experimentation to validate AI-driven solutions. Communicate technical progress, blockers, and implementation trade-offs effectively. Required Skills and Qualifications Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or a related field. 3–5 years of overall software engineering or application development experience. At least 1 year of hands-on experience building AI/ML or Generative AI applications. Strong programming experience in one or more of the following: Python Java or C#/.NET Node.js React or Angular SQL/NoSQL databases Practical experience with one or more of the following: Large Language Model (LLM) integration Retrieval-Augmented Generation (RAG) Prompt engineering Vector databases and semantic search AI/ML application development At least 1 year of exposure to cloud-native engineering using Azure, AWS, or GCP. Familiarity with cloud AI services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI. Understanding of REST APIs, microservices, object-oriented programming, data structures, algorithms, and software design principles. Experience with unit testing, debugging, version control, and code quality practices. Ability to work independently while collaborating effectively with cross-functional teams. Strong analytical, communication, problem-solving, and time-management skills. Preferred Qualifications Exposure to agentic AI frameworks such as LangChain, LangGraph, or equivalent tools. Familiarity with LangSmith, LangFuse, MLflow, or similar AI observability and experiment-tracking platforms. Experience with Agile methodologies, DevSecOps, GitHub, Azure DevOps (ADO), or SonarQube. Familiarity with CI/CD pipelines, automated testing, and cloud deployment practices. Experience using AI coding assistants and AI-enabled software development lifecycle (SDLC) tools. Understanding of architecture diagrams, sequence diagrams, data-flow diagrams, and entity-relationship diagrams. Work Requirements Ability to work from the local office at least 3 days per week. Willingness to travel up to 10%, depending on project and client requirements. Limited immigration sponsorship may be available. Ability to manage multiple priorities and deliver quality solutions within project timelines.

Questions from the bot

Do you have hands-on experience integrating Large Language Models (LLMs) into a business application? If so, what was the use case and which provider did you use?
Have you worked with vector databases or semantic search for data retrieval? If so, what tools did you implement and how did they improve accuracy?
Do you have experience using Python specifically for machine learning or AI tasks? If so, can you describe a project where you used it?

Timeline

2026-10-21 16:05:46
scored 75: The candidate is an exceptionally strong full-stack engineer with deep experience in building high-availability, complex data systems and B2B e-commerce platforms. However, the resume lacks direct hands-on evidence of working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or Python/ML frameworks, which are central to this Applied AI role.
2026-10-21 16:05:04
found Found via jobspy:linkedin