Agentic AI Intern

About CustomerInsights.AI, Inc

Founded in 2018 and headquartered in Scottsdale, Arizona, CustomerInsights.AI is a leader in AI-driven commercial analytics for the pharmaceutical and Life Sciences sectors. Our product, ciPARTHENON™, is a unified analytics cloud that integrates data, advanced analytics, and reporting, enabling clients to optimize sales, marketing, and patient engagement strategies.

About the Role

CustomerInsights.AI is seeking a Paid Agentic AI Intern to join our team in New Jersey for a 3-month internship. This is an exciting opportunity to apply artificial intelligence and machine learning engineering skills to real decisions impacting healthcare challenges today. The Agentic AI Intern will be responsible for developing, deploying, and optimizing AI systems that can transform raw data into intelligent insights and automated solutions to improve business outcomes and ultimately help deliver better patient care. High-performing interns may be considered for full-time employment based on individual performance and business needs.

Work Arrangement: Hybrid

Duties and responsibilities of the job:

Agentic AI Interns often make recommendations about AI strategies, architecture, model selection, and deployment strategies that enable companies to leverage artificial intelligence for competitive advantage and operational efficiency. As an intern, he/she will have the opportunity to refine their AI engineering skills and translate complex AI concepts into implementations that can be understood and utilized at multiple levels within the organization from the Executive team (C-Suite) who examine AI strategy at a high level, to the managers and directors who will implement AI-driven processes.

The AI intern will be responsible for:

• Emerging AI Techniques Research - Track new developments in agentic AI (frameworks, benchmarks, orchestration methods) and summarize which are relevant and practical for ciATHENA’s roadmap.
• Competitor Benchmarking - Research leading agentic AI products in the market and identify capabilities they offer that ciATHENA doesn’t. Deliver a clear, concise comparison report for leadership review.
• Gap Analysis for ciATHENA - Evaluate ciATHENA’s current capabilities against client and market needs. Identify and prioritize gaps based on real business impact, distinguishing must-haves from nice-to-haves.
• Build vs. Buy Recommendations - For each identified gap, assess whether it’s more efficient to build the capability in-house or adopt an existing framework/tool. Provide a simple cost-benefit view to support decision-making.
• Cross-Client Project Review - Analyze ongoing projects across clients (data warehousing, reporting, analytics) to identify the most time-consuming, repetitive tasks. Recommend which of these are strong candidates for automation through ciATHENA.
• Stress-Testing ciATHENA - Proactively test ciATHENA with ambiguous instructions, edge cases, and messy data to uncover failure points and inconsistencies — surfacing issues before clients do.
• Agent evaluation & observability harness - Score Athena’s LLM calls (NL→SQL accuracy, hallucination, latency, cost). The backbone that makes every other experiment provable.
• Self-healing data pipelines - Agents that detect and fix schema drift / data-quality issues autonomously, with guardrails.
• Text-to-SQL & semantic-layer robustness - schema-linking, join-grain-trap detection, semantic caching, auto-repair the highest-leverage reliability work.

Job qualifications and requirements:

A degree in the following subjects is beneficial in developing a career in AI:

· Data Science and Machine Learning

· Computer Science

· Statistics

· Analytics

· Mathematics

· Life Science experience is helpful – but not required

Technical skills:

· Hands-on experience in developing and fine-tuning generative AI models (LLMs, diffusion models, etc.)

· Experience in designing and implementing autonomous AI agents capable of decision-making, planning, and adapting to dynamic environments

· Knowledge of MLOps practices and AI model deployment strategies

· Experience with cloud AI platforms (AWS SageMaker, Google AI Platform, Azure ML, etc.)

· Strong programming skills in Python, with experience in AI/ML frameworks

· Understanding of transformer architectures, attention mechanisms, and modern AI model architectures

· Knowledge of AI ethics, bias detection, and res…