Lead AI Engineer

Precision Technologies; New Jersey; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Precision Technologies in the USA is seeking a Senior Lead AI/ML Architect Engineer with hands-on expertise in ML, Generative AI, LLMs, and MLOps to architect, develop, and deploy scalable enterprise AI solutions across hybrid environments.

You will lead design reviews, mentor teams, and collaborate with product, data, and cloud stakeholders to deliver production-ready AI applications using Python, PyTorch, Databricks, and cloud services.

Qualifications

• 15+ years of experience in AI/ML engineering, data science, software engineering, or related fields.
• Strong hands-on expertise in Python, ML, DL, and statistical modeling.
• Extensive experience with Generative AI, LLMs, RAG, prompts, and AI agents.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and/or Llama.
• Familiar with LangChain, LangGraph, LlamaIndex, or similar orchestration frameworks.
• Experience with Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate).
• Proficient with PyTorch, TensorFlow, Keras, Hugging Face, and Scikit-learn.
• Experience with Azure, AWS, and/or GCP AI/ML services.
• Strong experience with Databricks, Apache Spark, PySpark, Snowflake, and cloud data platforms.
• Experience implementing MLOps, MLflow, Docker, Kubernetes, CI/CD, model monitoring, and governance.
• Strong understanding of REST APIs, Microservices, Event-Driven Architecture, and enterprise integration.
• Excellent architecture, problem-solving, communication, and technical leadership.

Responsibilities

• Lead the architecture, design, development, and deployment of enterprise-scale AI/ML and Generative AI solutions.
• Design scalable LLM, RAG, Agentic AI, and AI-powered application architectures.
• Develop machine learning models for classification, regression, forecasting, recommendation, anomaly detection, NLP, and predictive analytics.
• Build enterprise GenAI applications using LLMs, Prompt Engineering, RAG, Vector Databases, AI Agents, and tool/function calling.
• Develop and optimize AI/ML pipelines using Python, PyTorch, TensorFlow, Scikit-learn, Spark, and Databricks.
• Design end-to-end MLOps pipelines covering model training, validation, deployment, monitoring, versioning, and continuous improvement.
• Integrate AI/ML solutions with enterprise applications, APIs, databases, and cloud services.
• Implement AI model optimization, scalability, observability, security, and cost-management strategies.
• Lead technical design reviews, architecture discussions, code reviews, and engineering best practices.
• Mentor AI/ML Engineers, Data Scientists, and developers while providing technical leadership.
• Collaborate with Product Managers, Data Engineers, Data Architects, Cloud Architects, and executive stakeholders.

Skills

15+ years experience

Python

Machine Learning

Deep Learning

Statistical Modeling

Generative AI & LLMs

Prompt Engineering

AI Agents

OpenAI/Azure OpenAI/Anthropic/Google/L

LangChain/LangGraph

Vector Databases

PyTorch/TensorFlow/Keras/Hugging Face/

Azure/AWS/GCP

Databricks/Spark/Snowflake

MLOps: MLflow/Docker/Kubernetes/CI/CD

REST APIs/Microservices

Tools

Databricks

Apache Spark

Snowflake

Kubernetes

Docker

REST APIs

Job description

Experience: 15+ Years (AI/ML Engineering, Data Science, Generative AI & AI Architecture Experience)

Employment Type: Full-Time (W2 Only)

Location: USA (Hybrid / Onsite)

Job Summary

We are seeking a highly experienced Senior Lead AI/ML Architect Engineer with strong hands-on expertise in Machine Learning, Generative AI, LLMs, RAG, Agentic AI, Python, Azure/AWS, Databricks, and MLOps to architect, develop, and deploy scalable enterprise AI solutions.

The ideal candidate will combine AI/ML architecture, hands-on engineering, cloud platforms, model development, AI application development, and technical leadership to deliver production-ready AI solutions across enterprise environments.

Key Responsibilities

• Lead the architecture, design, development, and deployment of enterprise-scale AI/ML and Generative AI solutions.
• Design scalable LLM, RAG, Agentic AI, and AI-powered application architectures.
• Develop machine learning models for classification, regression, forecasting, recommendation, anomaly detection, NLP, and predictive analytics.
• Build enterprise GenAI applications using LLMs, Prompt Engineering, RAG, Vector Databases, AI Agents, and tool/function calling.
• Develop and optimize AI/ML pipelines using Python, PyTorch, TensorFlow, Scikit-learn, Spark, and Databricks.
• Design end-to-end MLOps pipelines covering model training, validation, deployment, monitoring, versioning, and continuous improvement.
• Integrate AI/ML solutions with enterprise applications, APIs, databases, and cloud services.
• Implement AI model optimization, scalability, observability, security, and cost-management strategies.
• Lead technical design reviews, architecture discussions, code reviews, and engineering best practices.
• Mentor AI/ML Engineers, Data Scientists, and developers while providing technical leadership.
• Collaborate with Product Managers, Data Engineers, Data Architects, Cloud Architects, and executive stakeholders.

Required Skills

• 15+ years of experience in AI/ML Engineering, Data Science, Software Engineering, or related fields.
• Strong hands-on expertise in Python, Machine Learning, Deep Learning, and Statistical Modeling.
• Strong experience with Generative AI, LLMs, RAG, Prompt Engineering, and AI Agents.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and/or Llama.
• Strong experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
• Experience with Vector Databases such as Pinecone, FAISS, ChromaDB, or Weaviate.
• Strong ands-on experience with PyTorch, TensorFlow, Keras, Hugging Face, and Scikit-learn.
• Experience with Azure, AWS, and/or GCP AI/ML services.
• Strog experience with Databricks, Apache Spark, PySpark, Snowflake, and cloud data platforms.
• Experience implementing MLOps, MLflow, Docker, Kubernetes, CI/CD, model monitoring, and model governance.
• Strong understanding of REST APIs, Microservices, Event-Driven Architecture, and enterprise application integration.
• Strong architecture, problem-solving, communication, and technical leadership skills.

Eligibility & Compliance

• W2 Full-Time Only
• No C2C
• No Third-Party Vendors or Consultancy Profiles