About the role
AI Engineer – Job Description Position Summary We are seeking an innovative AI Engineer to design, develop, test, and deploy AI-powered solutions that drive business value through automation, advanced analytics, and intelligent applications. The AI Engineer will collaborate with cross-functional teams to build and test scalable machine learning and generative AI solutions that enhance operational efficiency and improve customer experiences. Key Responsibilities Design, develop, test, and deploy AI/ML and Generative AI solutions to solve complex business problems. Build and optimize data pipelines to support AI model training and inference. Develop and integrate Large Language Model (LLM) applications, AI agents, and Retrieval-Augmented Generation (RAG) solutions. Create scalable APIs and AI services for enterprise applications. Test agentic solutions and validate outputs to ensure accuracy, reliability, and expected behavior. Collaborate with data engineers, software developers, and business stakeholders to translate requirements into AI solutions. Evaluate, fine-tune, and monitor AI models for accuracy, performance, and reliability. Implement MLOps best practices for model deployment, testing, monitoring, and lifecycle management. Ensure AI solutions comply with enterprise security, governance, and responsible AI standards. Stay current with emerging AI technologies and recommend innovative approaches. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Strong programming skills in Python and SQL. Experience with Large Language Models (OpenAI, Anthropic, Llama, etc.) and prompt engineering. Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform. Experience with REST APIs, Git, and software development best practices. Strong analytical, problem-solving, and communication skills. Preferred Qualifications Experience with Snowflake, Databricks, or modern data platforms. Knowledge of vector databases, semantic search, and RAG architectures. Experience with AI orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel. Familiarity with Docker, Kubernetes, and CI/CD pipelines. Experience developing AI-powered analytics dashboards using Streamlit. Preferred Technical Skills Python SQL Machine Learning & Deep Learning Generative AI & Large Language Models (LLMs) Prompt Engineering RAG & Vector Databases Snowflake, Databricks Azure REST APIs & Microservices Git, Docker, Kubernetes Power BI, Tableau, Streamlit Agentic AI testing and output validation Success Measures Deliver scalable AI solutions that improve business outcomes. Automate manual processes through AI-driven workflows. Improve model accuracy, performance, and reliability. Successfully test agentic workflows and validate outputs against expected results. Partner effectively with stakeholders to translate business needs into AI capabilities. Continuously evaluate and adopt emerging AI technologies to drive innovation.