AI Technical Lead
The Judge Group · Charlotte, North Carolina, United States
FULL TIMEpermanent
Job Description
No Corps pleaseBusiness Title: Technical Lead - AI Platform
Ensure you read the information regarding this opportunity thoroughly before making an application.
JOB SUMMARY:Our client is seeking a Technical Lead - AI Platform to architect, build, and lead full-lifecycle AI/ML product development—from data pipelines and model training to GenAI integration and intelligent app deployment. This is an end-to-end role for a builder-leader: someone who thrives on writing production code, deploying machine learning systems, integrating LLMs, and leading an elite team of engineers and ML practitioners.
Key Responsibilities: Architect & Build Full-Stack AI SolutionsDesign and build end-to-end machine learning systems—including pipelines, feature stores, training/inference services, and monitoring.Architect scalable, modular applications that embed foundation models, retrieval-augmented generation (RAG), and agentic workflows directly into product experiences—all on Google Cloud Platform (GCP) or Oracle Cloud Infrastructure (OCI).Develop privacy-preserving ML systems that align with food industry compliance and traceability standards.Build explainable AI frameworks to enable business stakeholders to trust and validate model outputs.Design AI architectures that deliver tenant-aware intelligence while ensuring strict data isolation and performance SLAs across our multi-tenant SaaS platform.
Hands-On EngineeringDevelop robust data pipelines using BigQuery, Dataflow, and Apache Beam.Train, tune, and deploy ML models using TensorFlow, PyTorch, and Scikit-learn.Build full-stack AI-native applications with Python, Java, React/Angular, and GCP-native services. ● Implement robust MLOps pipelines that ensure reproducible training, CI/CD deployment, cost-efficient scaling, and real-time model monitoring. GenAI & AI Agent DevelopmentIntegrate GenAI features: RAG pipelines, content summarization, Q&A, semantic search synthetic data generation, and multi-turn chat interfacesDesign and develop AI agents and copilots using LangChain, CrewAI, and Vertex AI to automate complex business processes.Use vector databases (FAISS, Pinecone) to build domain-specific LLM workflows.Prototype and deploy multi-agent systems for autonomous decision-making and workflow execution across supply chain, pricing, traceability, and forecasting.
Technical Leadership● Lead a high-impact team of ML engineers and AI developers.● Set technical strategy, define best practices, and guide architectural decision-making.● Work cross-functionally with Product, Data Science, and Executive teams to shape AI innovation and delivery.
What you’ll need: ● 10+ years in software/ML engineering; 5+ years leading architecture and engineering teams.● Proven experience building production-ready AI/ML pipelines and applications end-to-end.● Expertise in GenAI frameworks (OpenAI, Vertex AI), multi-agent architectures, and MLOps tooling.● Experience operationalizing LLMs for enterprise use cases: hallucination reduction, security, cost optimization, and monitoring.● Track record of shipping high-quality intelligent products quickly and at scale. xzbcwsv ● Strong team leadership, communication, and cross-functional collaboration skills.
Tech Stack: Languages & Frameworks: ● Python, Java, SQL, JavaScript/TypeScript● TensorFlow, PyTorch, Scikit-learn● React, Angular Cloud Platform:● GCP – Vertex AI, BigQuery, Cloud Functions, Cloud Run, Dataflow, Pub/Sub● OCI – Data Science, Autonomous Data Warehouse, Functions, Container Engine for Kubernetes (OKE), Data Flow, and Streaming
Data & MLOps: ● BigQuery, AlloyDB, MongoDB, Redis● MLflow, Kubeflow, Airflow● Docker, Kubernetes, GitHub Actions, Terraform● GenAI & Agents:● Vertex AI Gemini, OpenAI, Claude● LangChain, LlamaIndex, FAISS, Pinecone● RAG pipelines, autonomous agents, multi-agent orchestration, memory modules, tool use, prompt chaining
Dev Tools: ● GitHub Copilot, ChatGPT, Cursor AI, Locofy
Ensure you read the information regarding this opportunity thoroughly before making an application.
JOB SUMMARY:Our client is seeking a Technical Lead - AI Platform to architect, build, and lead full-lifecycle AI/ML product development—from data pipelines and model training to GenAI integration and intelligent app deployment. This is an end-to-end role for a builder-leader: someone who thrives on writing production code, deploying machine learning systems, integrating LLMs, and leading an elite team of engineers and ML practitioners.
Key Responsibilities: Architect & Build Full-Stack AI SolutionsDesign and build end-to-end machine learning systems—including pipelines, feature stores, training/inference services, and monitoring.Architect scalable, modular applications that embed foundation models, retrieval-augmented generation (RAG), and agentic workflows directly into product experiences—all on Google Cloud Platform (GCP) or Oracle Cloud Infrastructure (OCI).Develop privacy-preserving ML systems that align with food industry compliance and traceability standards.Build explainable AI frameworks to enable business stakeholders to trust and validate model outputs.Design AI architectures that deliver tenant-aware intelligence while ensuring strict data isolation and performance SLAs across our multi-tenant SaaS platform.
Hands-On EngineeringDevelop robust data pipelines using BigQuery, Dataflow, and Apache Beam.Train, tune, and deploy ML models using TensorFlow, PyTorch, and Scikit-learn.Build full-stack AI-native applications with Python, Java, React/Angular, and GCP-native services. ● Implement robust MLOps pipelines that ensure reproducible training, CI/CD deployment, cost-efficient scaling, and real-time model monitoring. GenAI & AI Agent DevelopmentIntegrate GenAI features: RAG pipelines, content summarization, Q&A, semantic search synthetic data generation, and multi-turn chat interfacesDesign and develop AI agents and copilots using LangChain, CrewAI, and Vertex AI to automate complex business processes.Use vector databases (FAISS, Pinecone) to build domain-specific LLM workflows.Prototype and deploy multi-agent systems for autonomous decision-making and workflow execution across supply chain, pricing, traceability, and forecasting.
Technical Leadership● Lead a high-impact team of ML engineers and AI developers.● Set technical strategy, define best practices, and guide architectural decision-making.● Work cross-functionally with Product, Data Science, and Executive teams to shape AI innovation and delivery.
What you’ll need: ● 10+ years in software/ML engineering; 5+ years leading architecture and engineering teams.● Proven experience building production-ready AI/ML pipelines and applications end-to-end.● Expertise in GenAI frameworks (OpenAI, Vertex AI), multi-agent architectures, and MLOps tooling.● Experience operationalizing LLMs for enterprise use cases: hallucination reduction, security, cost optimization, and monitoring.● Track record of shipping high-quality intelligent products quickly and at scale. xzbcwsv ● Strong team leadership, communication, and cross-functional collaboration skills.
Tech Stack: Languages & Frameworks: ● Python, Java, SQL, JavaScript/TypeScript● TensorFlow, PyTorch, Scikit-learn● React, Angular Cloud Platform:● GCP – Vertex AI, BigQuery, Cloud Functions, Cloud Run, Dataflow, Pub/Sub● OCI – Data Science, Autonomous Data Warehouse, Functions, Container Engine for Kubernetes (OKE), Data Flow, and Streaming
Data & MLOps: ● BigQuery, AlloyDB, MongoDB, Redis● MLflow, Kubeflow, Airflow● Docker, Kubernetes, GitHub Actions, Terraform● GenAI & Agents:● Vertex AI Gemini, OpenAI, Claude● LangChain, LlamaIndex, FAISS, Pinecone● RAG pipelines, autonomous agents, multi-agent orchestration, memory modules, tool use, prompt chaining
Dev Tools: ● GitHub Copilot, ChatGPT, Cursor AI, Locofy
Details
| Company | The Judge Group |
| Location | Charlotte, North Carolina, United States |
| Type | FULL TIME |
| Niche | general |
| Experience | permanent |