We are seeking a skilled and experienced AI Engineer with expertise in Python, Machine Learning, Deep Learning, and full-stack software development. The ideal candidate will have a strong background in machine learning and a deep understanding of Natural Language Processing and will be equally comfortable building the front-end and back-end of the applications that put those models to work including agentic and generative AI (GenAI) solutions such as Retrieval-Augmented Generation (RAG) systems to develop advanced solutions for intelligent document processing. The role involves leveraging advanced analytical techniques and modern software engineering practices to drive data-driven decision-making and deliver innovative, end-to-end solutions to our Internal and External Customers.

Responsibilities:

• Design, develop, and implement advanced machine learning models and algorithms to solve complex business problems.
• Leverage expertise in Python, Machine Learning to develop cutting-edge data-driven solutions.
• Utilize NLP and NLU techniques to extract insights, classify, and process information from unstructured text data in documents.
• Design, build, and deploy agentic AI and generative AI (GenAI) applications, including Retrieval-Augmented Generation (RAG) pipelines and LLM-powered agents, to automate workflows and enhance decision-making.
• Build and maintain full-stack applications — front-end interfaces and back-end services/APIs — that deliver AI/ML and GenAI capabilities to end users.
• Conduct data analysis, pre-processing, and modeling to extract valuable insights and drive data-driven decision-making.
• Collaborate with cross-functional teams to understand business requirements and translate them into actionable AI/ML solutions.
• Stay up to date with the latest advancements in AI/ML technologies, frameworks, and tools, and proactively learn and adopt new technologies to enhance our offerings.
• Communicate effectively with stakeholders, presenting findings, recommendations, and project progress in a clear and concise manner.

Primary Skills:

• Machine Learning (e.g., CNN, RNN, GAN, Transformers, Encoder-Decoder architectures, NLTK, Transformers).
• Knowledge and experience in Python.
• Full-Stack Software Development: Proficiency building complete web applications, including front-end (e.g., JavaScript/TypeScript, React, HTML/CSS) and back-end development (e.g., Python frameworks such as FastAPI, Flask, or Django; RESTful/GraphQL API design; SQL/NoSQL databases).
• Agentic AI & Generative AI: Hands-on experience designing, building, and deploying agentic AI systems and LLM-powered applications, including orchestration and agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, LangGraph, AutoGen, CrewAI), vector databases (e.g., FAISS, Pinecone, Azure AI Search), and prompt engineering.
• Data Analysis and Modeling.
• AI/ML Architecture: Design and develop scalable and efficient AI/ML architectures to support the deployment of machine learning models.
• Data Engineering: Work closely with data engineers to ensure the availability, quality, and reliability of data required for AI/ML projects.
• RAG Pipelines: Implement robust and reliable RAG (Retrieval - Augmented Generation) pipelines to automate the end-to-end AI/ML workflow.
• MLOps: Implement MLOps practices to streamline the development, deployment, and management of AI/ML models.
• Azure AI Tools: Experience with Azure AI tools and services, such as Azure Machine Learning, Azure Databricks, and Azure Cognitive Services.
• Research and Problem-Solving.

Qualification & Requirements:

• Bachelor's degree or higher in Computer Science, AI/ML, or a related field.
• Minimum of 2+ years of relevant professional experience in Python, Machine Learning, Deep Learning.
• Strong expertise in data analysis, modeling, and machine learning techniques (e.g., regression, classification, clustering, deep learning).
• Proficiency in Python and relevant libraries/frameworks for NLP (e.g., NLTK, spaCy, Transformers).
• Proficiency in Python and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Demonstrated experience building and deploying full-stack applications (front-end and back-end) that integrate AI/ML or GenAI capabilities.
• Practical, hands-on experience developing agentic AI and GenAI applications using RAG architectures, LLM orchestration frameworks, and vector databases.
• Experience in working with large and complex datasets, data pre-processing, and feature engineering.
• Solid understanding of statistical concepts and their applications in data analysis.
• Proven track record of delivering successful AI/ML projects and driving business impact.
• Excellent communication, presentation, and documentation skills.
• Strong problem-solving abilities and a proactive attitude towards learning and adopting new technologies.
• Ability to work independently, manage multiple projects simultaneously, and collaborate effectively with diverse stakeholders.