N
Applied AI Engineer
N2P Systems
2 hours ago
Full-time
On-site
Nashville, Tennessee, United States
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.
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.