Gen AI and Agentic AI Engineer

Infosys offers an onsite Gen AI and Agentic AI Engineer role in Charlotte, NC that centers on developing, deploying, and refining data-driven models and analytics solutions, including LLM-based approaches. This position emphasizes data readiness, governance, and knowledge transfer across projects, delivering scalable analytics that align with business needs.

Responsibilities

• Develop data preparation workflows while identifying patterns or anomalies in datasets.
• Ensure data readiness to support advanced modeling initiatives.
• Build models for complex use cases such as forecasting and LLM-based solutions, refine algorithms to meet business needs, and deploy them into scalable, production-ready systems.
• Test and optimize algorithms for performance, reliability, and scalability, while guiding teammates in best practices.
• Design predictive models and data-driven analyses to address business challenges.
• Assemble, 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 enhancing analytics including LLMs and developing cost-effective innovations.
• Define analytics problems for projects; conduct visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models and implement improvements to sustain accuracy and reliability.
• Apply governance controls to mitigate risks and ensure compliance.
• Analyze performance trends, recommend improvements, and document discrepancies for escalation.
• Maintain thorough documentation and participate in knowledge transfer sessions.
• Engage with stakeholders to refine requirements, share insights, and guide model implementation.
• Apply the predefined quality measurement framework at the task level 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, proofs of concept, and innovations in non-ML, ML, deep learning, or LLM models.
• Participate in analytics training and content creation, supporting ongoing learning within the team.
• Provide input for segment and unit-level business plans.
• Deliver scalable, high-quality analytics solutions aligned to business needs.
• Demonstrate a knack for optimization, deployment, and performance improvement of models.
• Drive innovation through advanced analytics, automation, and thought leadership.
• Enable team growth through knowledge sharing, training, and standardization.
• Support business planning with data-driven insights.

Technologies

• SAS
• R
• Python

Your contribution to the team

• Deliver scalable, high-quality analytics solutions aligned to business needs.
• Apply optimization, deployment, and performance improvements to 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.