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Applied AI Engineering Lead
N2P Systems
3 hours ago
Full-time
On-site
Nashville, Tennessee, United States
Applied AI Engineering Lead
The candidates will need to be local to either Nashville, TN or Tampa, FL with hybrid set up (2-3 days on sight).
Scroll down the page to see all associated job requirements, and any responsibilities successful candidates can expect.
Job Description We are looking for an experienced
Applied AI Engineering Lead with 6 to 8 years of overall experience
to actively engage in the engineering craft and take a hands-on approach to multiple high-visibility projects. The role focuses on delivering high-quality, outcome-focused solutions while leveraging AI and agentic tools across the engineering lifecycle. Responsibilities Drive engineering solutions that deliver customer and business outcomes. Serve as a technical advocate for products. Lead requirement analysis, low-level architecture, component design, development, testing, integrations and support. Maintain architecture and technical-stack integrity. Manage dependencies, code design, implementation, quality, data and ongoing operations. Remain hands-on with modern languages, frameworks and AI-enabled engineering practices. Create technical specifications and scalable code. Review code and mentor other engineers. Develop AI-built prototypes for rapid experimentation. Collaborate with customers, product teams and cross-functional teams. Apply AI and Agentic SSDLC practices. Use AI tools for code generation, review, testing and documentation. Requirements Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or related discipline. 6–8 years
of experience with most of: Angular React NodeJS Python C# .NET Java SQL/NoSQL PyTorch TensorFlow LangChain LangGraph Unit testing frameworks 2+ years
building AI/ML applications. Hands-on GenAI experience with: LLM integration OpenAI / Anthropic / open-source models RAG Prompt engineering Vector databases 2+ years
cloud-native engineering with Azure, AWS or GCP. Experience with Azure OpenAI, AWS Bedrock or Vertex AI. Experience establishing engineering standards and mentoring team members. Knowledge of OOP/OOD, data structures, algorithms, system/data-flow diagrams. Experience with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow. Experience with agentic AI frameworks such as LangFuse, LangSmith or equivalent. Ability to work in the local office a minimum of
3 days per week . xsgimln 0–10% travel.
Scroll down the page to see all associated job requirements, and any responsibilities successful candidates can expect.
Job Description We are looking for an experienced
Applied AI Engineering Lead with 6 to 8 years of overall experience
to actively engage in the engineering craft and take a hands-on approach to multiple high-visibility projects. The role focuses on delivering high-quality, outcome-focused solutions while leveraging AI and agentic tools across the engineering lifecycle. Responsibilities Drive engineering solutions that deliver customer and business outcomes. Serve as a technical advocate for products. Lead requirement analysis, low-level architecture, component design, development, testing, integrations and support. Maintain architecture and technical-stack integrity. Manage dependencies, code design, implementation, quality, data and ongoing operations. Remain hands-on with modern languages, frameworks and AI-enabled engineering practices. Create technical specifications and scalable code. Review code and mentor other engineers. Develop AI-built prototypes for rapid experimentation. Collaborate with customers, product teams and cross-functional teams. Apply AI and Agentic SSDLC practices. Use AI tools for code generation, review, testing and documentation. Requirements Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or related discipline. 6–8 years
of experience with most of: Angular React NodeJS Python C# .NET Java SQL/NoSQL PyTorch TensorFlow LangChain LangGraph Unit testing frameworks 2+ years
building AI/ML applications. Hands-on GenAI experience with: LLM integration OpenAI / Anthropic / open-source models RAG Prompt engineering Vector databases 2+ years
cloud-native engineering with Azure, AWS or GCP. Experience with Azure OpenAI, AWS Bedrock or Vertex AI. Experience establishing engineering standards and mentoring team members. Knowledge of OOP/OOD, data structures, algorithms, system/data-flow diagrams. Experience with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow. Experience with agentic AI frameworks such as LangFuse, LangSmith or equivalent. Ability to work in the local office a minimum of
3 days per week . xsgimln 0–10% travel.