Gen/Agentic AI Engineer

Onsite at Infosys in Irving, Texas, this role centers on building, validating, and deploying data driven analytics and AI models, including forecasting and large language model based solutions. The position emphasizes data readiness, governance, and close collaboration with stakeholders to translate business needs into scalable analytics capabilities.

Responsibilities

• Design data preparation workflows while identifying patterns and anomalies during the process.
• Ensure data is ready for advanced modeling activities.
• Develop models for complex use cases such as forecasting and LLM based solutions, refine algorithms to meet business needs, and ensure deployment into scalable, production ready systems.
• Test and optimize algorithms for performance, reliability, and scalability, while guiding team members in best practices.
• Design and implement predictive models and data driven analyses to address business challenges.
• Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
• Leverage SAS, R and Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while expanding analytics including LLMs and delivering innovative, cost effective solutions.
• Define analytics problems for projects and execute visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models and implement improvements for accuracy and reliability.
• Apply governance controls to mitigate risks and ensure compliance.
• Analyze performance trends, recommend improvements, and document discrepancies for escalation.
• Maintain comprehensive documentation standards and participate in knowledge transfer sessions.
• Engage with stakeholders to refine requirements, provide insights, and guide model implementation.
• Apply the predefined quality measurement framework at the level of individual tasks within projects.
• Deploy complex analytics tools or multi system integrations and validate deployment success.
• Develop scripts or templates to streamline repeated deployment tasks.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Contribute to thought leadership through papers and conceptual work in non-ML, ML, deep learning, or LLM models and proofs of concepts.
• Participate in and deliver analytics training, contributing to content creation.
• Provide input for segment and unit level business plans.

Technologies

• SAS
• R
• Python

Your Contribution to the Team

• Deliver scalable, high quality analytics solutions aligned to business needs.
• Own optimization, deployment, and performance improvements of models.
• Drive innovation through advanced analytics, automation, and thought leadership.
• Foster team growth through knowledge sharing, training, and standardization.
• Support business planning with data driven insights.