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# Full Stack AI Engineer - Agentic AI | LLMs | Python

- **Company:** Argyll Info Tech Inc.,
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Frameworks, Microsoft Azure, Big Data, Computer Programming, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Graph Database, Python (Programming Language), Machine Learning, Natural Language Processing, NLTK (NLP Analysis), Performance Tuning, Tensorflow, Azure Machine Learning, SQL Databases, Data Streaming, Scripting, Enterprise Software Applications, Data Ingestion, Pytorch, LangChain, Large Language Models, Prompt Engineering, Apache Spark, Spring-boot, Deep Learning, Generative AI, Agentic-AI, Microsoft Fabric, Data Lakes, AngularJS, Scikit Learn, Kubernetes, HuggingFace, Machine Learning Operations, Virtual Agents, Spacy, Semantic Kernel, Docker, AI Co-pilot, Unsupervised Learning, Databricks, Microservices
- **Published:** October 26, 2026
- **Apply:** https://www.careerbuilder.com/job-details/full-stack-ai-engineer-agentic-ai-llms-python-fl--6c4d54d2-1ae0-4e26-9ef3-c3ea7dee9796

## About the Role

Artificial Intelligence (AI), Python Programming/Scripting Language, Python Programming/Scripting Language, Deep Learning, Natural Language Processing (NLP), Artificial Intelligence (AI), Forecasting, Continuous Improvement, Computer Programming, SQL (Structured Query Language)

## Description

Minimum Experience: 5+ years of relevant experience and 10+ years of overall experience
Certification: Not Required
Drug Test: No
Must-Have Skills

 * Artificial Intelligence (AI)
 * Python

Nice-to-Have Skills

 * Java Spring Boot
 * Angular

Detailed Job Description

 * Design and develop AI/ML solutions using supervised and unsupervised learning, deep learning, NLP, time series forecasting, and anomaly detection techniques to address business challenges.
 * Build Generative AI applications leveraging LLMs, prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), and AI agent frameworks.
 * Experience working in the banking domain.
 * Develop and maintain end-to-end AI pipelines, covering data ingestion, preprocessing, model training, deployment, monitoring, and continuous improvement.
 * Demonstrate strong programming expertise in Python and SQL, with hands-on experience in ML libraries such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, SpaCy, and NLTK.
 * Work with large-scale data ecosystems, including ETL processes, data lakes, data warehouses, streaming platforms, and tools such as Spark, Databricks, or Microsoft Fabric.
 * Implement MLOps best practices, including CI/CD pipelines, model governance, explainability, monitoring, Docker-based containerization, and Kubernetes orchestration.
 * Deploy AI models through APIs and microservices, ensuring seamless integration with enterprise applications, systems, and cloud platforms.
 * Utilize cloud-based AI services on Azure or AWS, including platforms such as Azure Machine Learning and Amazon SageMaker.
 * Collaborate with business and technology stakeholders to translate business requirements into scalable AI solutions while tracking ROI and value realization.
 * Contribute to AI innovation and best practices through reusable frameworks, AI copilots, semantic models, knowledge graphs, LangChain/Semantic Kernel orchestration, and synthetic data techniques.