AI Solution Engineer

We are seeking a talented and passionate AI Solution Engineer to design, develop, and implement end-to-end AI solutions that solve complex business challenges and enhance products and services. This role requires expertise across artificial intelligence, machine learning, generative AI, data engineering, and enterprise data platforms. The ideal candidate will be comfortable working from raw data through solution development, evaluation, and deployment while collaborating with both technical and business stakeholders.

Duties

• Design, develop, deploy, and optimize machine learning, generative AI, and Retrieval-Augmented Generation (RAG) solutions.
• Build AI applications and models, including predictive analytics, classification, recommendation engines, and natural language processing solutions.
• Evaluate AI solutions for performance, accuracy, bias, reliability, and opportunities for improvement.
• Develop and maintain scalable data pipelines, ETL/ELT processes, and data preparation workflows for structured and unstructured data.
• Perform data profiling, cleansing, validation, transformation, and quality management to support analytics and AI initiatives.
• Support enterprise data architectures and platforms, including data lakes, lakehouses, and data warehouses.
• Integrate and manage data from cloud, on-premises, API, and third-party systems.
• Apply best practices for data governance, metadata management, lineage, security, and Responsible AI.

Artificial Intelligence (AI), Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), Predictive Modeling, Performance Analysis, Data Management, Unstructured Data, Data Processing, Database Extract Transform and Load (ETL), * Experience developing and implementing machine learning and generative AI solutions.

• Experience designing and developing Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources.
• Strong knowledge of data engineering principles, including ETL/ELT, data pipelines, and data quality management.
• Experience working with enterprise data platforms, including data lakes, lakehouses, and data warehouses.
• Proficiency in Python, SQL, PySpark, REST APIs, and modern cloud-based AI and data technologies.
• Understanding of data governance, metadata management, data lineage, data security, and Responsible AI best practices.
• Strong analytical and problem-solving skills.
• Strong written and verbal communication skills with the ability to collaborate effectively across technical and business teams.

Preferred Skills

• Experience building and optimizing predictive models, classification models, recommendation engines, and natural language processing applications.
• Experience integrating data from multiple enterprise environments, including cloud, on-premises, APIs, and third-party systems.
• Experience evaluating and improving AI model performance, accuracy, reliability, and bias.
• Experience supporting end-to-end AI solution development, from data ingestion and preparation through deployment and ongoing optimization.
• Familiarity with scalable enterprise data architectures and modern cloud-based AI and analytics ecosystems.