Gen AI and Agentic AI Engineer

Infosys • Charlotte, NC

1d • Onsite

About The Position

In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below: Develop data preparation tasks, while identifying patterns or anomalies. Ensure data readiness for advanced modeling. Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions. Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in 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 tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions. Define analytics problems for projects; 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, while participating in knowledge transfer sessions. Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models. Apply the predefined quality measurement framework at an individual task level in the project. Deploy complex analytics tools or multi-system integration, while validating deployment success. Participate in developing scripts or templates for repeated deployments tasks. Contribute to analytic solutions, IP asset creation, and training initiatives. Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concept. Participate in and deliver analytics training, while contributing to content creation. Provide input for segment and unit-level business plans. Your contribution to the team: Deliver scalable, high-quality analytics solutions aligned to business needs. A knack for optimization, deployment and performance improvement of models. The ability to 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. Overview The Infosys Data and Analytics (DNA) unit is at the forefront of transforming data into actionable insights, driving business growth and operational efficiency. We specialize in leveraging advanced AI and analytics to create innovative solutions that address complex business challenges. Our team is dedicated to pioneering the future of data-driven decision-making, enabling organizations to unlock new opportunities and achieve sustainable success. Join us to be part of a dynamic team that is revolutionizing the way businesses harness the power of data and AI. At Infosys DNA, you'll have the opportunity to work with cutting-edge technologies, collaborate with industry experts, and contribute to transformative projects that shape the future of business. We are committed to fostering a culture of continuous learning and growth, ensuring that our team members thrive in a dynamic and supportive environment. If you're passionate about AI and eager to make a significant impact, the Infosys DNA unit is the perfect place for you to grow and excel.

Requirements

• Experience in cloud platforms (Azure, GCP) and their AI/ML services.
• Experience in Generative AI, LLMs, and agentic frameworks.
• Experience in Agentic AI, Python Full stack, Rest API, MCP, Lang Chain
• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply.

Nice To Haves

• Experience in Big Data technologies (e.g., BigQuery, Hadoop).
• Expertise in ML model development, data engineering, and software engineering principles.
• Knowledge of MLOps and AI/ML deployment (e.g., SageMaker, Snowflake).
• Familiarity with CI/CD, DevOps, and automation tools in AI/ML contexts.

Responsibilities

• Develop data preparation tasks, while identifying patterns or anomalies.
• Ensure data readiness for advanced modeling.
• Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.
• Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in 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 tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
• Define analytics problems for projects; 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, while participating in knowledge transfer sessions.
• Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
• Apply the predefined quality measurement framework at an individual task level in the project.
• Deploy complex analytics tools or multi-system integration, while validating deployment success.
• Participate in developing scripts or templates for repeated deployments tasks.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concept.
• Participate in and deliver analytics training, while contributing to content creation.
• Provide input for segment and unit-level business plans.
• Deliver scalable, high-quality analytics solutions aligned to business needs.
• 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.

Benefits

• Medical/Dental/Vision/Life Insurance
• Long-term/Short-term Disability
• Health and Dependent Care Reimbursement Accounts
• Insurance (Accident, Critical Illness , Hospital Indemnity, Legal)
• 401(k) plan and contributions dependent on salary level
• Paid holidays plus Paid Time Off

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level