GenAI Engineer

Role Description: The GenAI Engineer will design, build, and deploy generative AI solutions that enhance and automate integration workflows for client systems. Day-to-day responsibilities include developing and fine-tuning AI models, creating APIs and services that connect these models to existing applications, and collaborating with product, integration, and data teams to understand requirements and deliver production-ready solutions. The role involves evaluating new GenAI tools and frameworks, optimizing performance and reliability, and ensuring secure, responsible use of AI technologies. Data Analytics & Engineering 5+ years of experience in data analytics, data engineering, data science, or related technology roles. Strong experience working with large datasets and complex data analysis. Experience designing and maintaining data pipelines, data integration processes, and reporting solutions. Solid understanding of data modeling, data transformation, and data quality management. Experience working with structured and unstructured data sources. Programming & Solution Development Strong programming skills in one or more modern languages such as Python, Java, or similar. Experience developing scalable applications, automation solutions, or data-driven platforms. Familiarity with modern software development practices and source control tools. Analytics, AI & Machine Learning Experience applying machine learning, statistical analysis, or predictive analytics to business problems. Understanding of model development, validation, deployment, and monitoring processes. Exposure to natural language processing, generative AI, or advanced analytics techniques. Experience translating data into actionable business insights. Cloud & Platform Technologies Experience working with public cloud platforms and cloud-native services. Familiarity with infrastructure automation, containerization, and CI/CD practices. Experience supporting data, analytics, or AI workloads in cloud environments. Reporting & Visualization Experience developing dashboards, reports, and business intelligence solutions. Ability to communicate technical findings to business audiences through visualizations and presentations. Experience defining and measuring operational or business performance metrics. Business & Stakeholder Engagement Experience working with cross-functional teams and business stakeholders. Ability to gather requirements and translate them into practical technology solutions. Experience managing workstreams, coordinating deliverables, and driving outcomes. Strong written and verbal communication skills. Good-to-Have Skills Enterprise Platforms Experience working with enterprise applications and large-scale business systems. Exposure to ERP platforms, enterprise data integration, or operational reporting environments. Knowledge of enterprise monitoring, automation, or compliance processes. SAP data integration, reporting, automation, or analytics experience. Advanced Analytics Experience with model explainability techniques. Knowledge of statistical experimentation and analytical methodologies. Exposure to retrieval-augmented generation (RAG), vector databases, or knowledge-based AI solutions. Experience with streaming, near real-time, or event-driven analytics architectures. Financial & Operational Analytics Experience in reconciliation, controls, risk analysis, or operational reporting environments. Exposure to finance, banking, healthcare, manufacturing, or other large enterprise domains. Experience identifying and managing data quality issues, exceptions, and operational risks. Automation & Process Optimization Experience with workflow automation, robotic process automation, or related technologies. Experience improving business processes through automation and analytics. Exposure to orchestration platforms and enterprise automation frameworks. Leadership Experience mentoring team members and supporting technical delivery. Exposure to project leadership, stakeholder management, and global team collaboration