AI Engineer Analytics

Infosys is seeking an AI Engineer/Analytics professional in Dallas, TX (onsite) to build predictive and advanced analytics capabilities, from data preparation through deployment, with ongoing model governance and improvement. The role emphasizes forecasting, LLM-based approaches, scalable production delivery, and data-driven insights that support business outcomes.

Responsibilities

• Develop data preparation tasks, including identification of patterns or anomalies.
• Ensure data readiness for advanced modeling and analytics execution.
• Build models for complex use cases such as forecasting and LLM-based solutions, refining algorithms to align with business needs and enabling scalable, production-ready deployment.
• Perform testing and optimize algorithms for performance, reliability, and scalability.
• Provide guidance to team members by sharing best practices.
• Design and develop predictive models and data-driven analyses to address business challenges.
• Build, evaluate, and deploy models; standardize code; and contribute to knowledge management.
• Leverage SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, including analytics enhancements involving LLMs, with a focus on innovative and cost-effective solutions.
• Define analytics problems for projects and support execution of visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models and implement improvements to strengthen accuracy and reliability.
• Apply governance controls to mitigate risks and support compliance requirements.
• Analyze performance trends, recommend improvements, and document discrepancies for escalation.
• Maintain comprehensive documentation and participate in knowledge transfer sessions.
• Engage with stakeholders to refine requirements, provide insights, and guide implementation.
• Apply a predefined quality measurement framework at the individual task level in the project.
• Deploy complex analytics tools or multi-system integrations, validating deployment success.
• Participate in developing scripts or templates to support repeated deployment tasks.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Support thought leadership through papers, innovative models spanning non-ML, ML, deep learning, and LLM proof-of-concepts.
• Participate in analytics training and contribute to content creation.
• Provide input for segment and unit-level business plans and support business planning with data-driven insights.

Required Technologies

• SAS
• R
• Python
• LLMs
• Non-ML
• ML
• Deep learning

Role Focus

The position centers on delivering scalable, high-quality analytics solutions aligned to business needs, including optimization, deployment, and ongoing model performance improvement. It also emphasizes knowledge sharing, training, and standardization to enable team growth, while supporting business planning through data-driven insights.