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Applied AI Engineering Lead

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Onsite

Applied AI Engineering Lead

N2P Systems

Applied AI Engineering Lead

Skills

Google Cloud PlatformSQL QueriesReactNodePythonData ScienceJavaDevOpsC#.NETPyTorchTensorFlowMachine LearningAIAWSGitHubAzure

24 days ago

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Important information


Contract type:

Freelance / Contract

Location:

Nashville, TN, USA

Work mode:

Onsite

Published on:

3 October 2026

What they need


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).

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 .
  • 0–10% travel.

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