Agentic AI Engineer

About this role

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.   Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Job Title: Senior Agentic AI Engineer / AI-ML Engineer Location Remote Experience 5–10+ Years About the Role We are seeking a highly skilled Agentic AI Engineer to design and build intelligent automation solutions for large-scale enrollment and benefits administration systems. The platform currently processes over 15 million enrollment-related transactions , with approximately 80% of scenarios handled through deterministic rule-based automation and the remaining 20% requiring manual intervention . The objective of this role is to leverage Agentic AI, LLMs, and machine learning techniques to automate complex exception handling, accelerate rule creation, reduce testing effort, and continuously evolve the decisioning framework as new scenarios emerge in production. The ideal candidate will have strong expertise across AI/ML engineering, full-stack development, MLOps, workflow orchestration, and rule-engine modernization . Key Responsibilities Agentic AI & Intelligent Automation • Design and develop Agentic AI solutions to automate complex enrollment change scenarios currently requiring manual intervention. • Build AI-powered agents capable of analyzing exceptions, recommending actions, and creating new rule definitions from emerging production scenarios. • Develop scalable orchestration frameworks using LangGraph, LangChain, and modern AI agent architectures.

Rule Engine Modernization • Work on next-generation rule-based systems that combine deterministic business rules with probabilistic AI reasoning. • Convert and operationalize business rules represented in DMN/XML formats using tools such as PyDMN. • Enable continuous learning mechanisms where new production cases can be analyzed and translated into new business rules.

Test Automation & Scenario Generation • Develop AI-assisted test case generation frameworks for highly complex rule environments containing hundreds of business scenarios and edge cases. • Identify unseen exception paths and generate test scenarios that may not have been anticipated by SMEs. • Reduce testing cycles and accelerate deployment through intelligent validation and simulation.

Machine Learning & Data Science • Build models and decision-support systems for scenario classification, exception handling, and rule recommendation. • Evaluate the stability, reliability, and performance of LLM-driven workflows. • Design feedback loops for continuous improvement of AI-generated recommendations.

MLOps & Productionization • Implement scalable MLOps pipelines for model deployment, monitoring, and governance. • Build observability and evaluation frameworks for AI agents and rule engines. • Ensure reliability, scalability, and compliance in production environments processing millions of transactions.

Required Skills AI & Machine Learning • Strong experience in Machine Learning, Generative AI, and Agentic AI systems. • Experience building AI agents using: • LangGraph • LangChain • OpenAI / Anthropic / Azure OpenAI ecosystems

• Knowledge of probabilistic reasoning and AI-driven decision systems.

Programming & Engineering • Expert-level Python development skills. • Experience building production-grade applications and APIs. • Strong software engineering practices including testing, CI/CD, and code quality.

Rule Engines & Decision Systems • Experience with business rule engines and decision management platforms. • Understanding of DMN (Decision Model and Notation) and XML-based rule representations. • Experience with PyDMN or similar decision automation frameworks preferred.

MLOps & Cloud • Experience with model deployment, monitoring, and lifecycle management. • Knowledge of containerization and cloud-native architectures. • Familiarity with ML observability and evaluation frameworks.

Data Science • Strong analytical and problem-solving skills. • Experience working with large-scale transactional systems and operational data.

Preferred Qualifications • Experience in healthcare, insurance, benefits administration, or enrollment platforms. • Experience processing high-volume transactional workloads (10M+ transactions). • Knowledge of decision intelligence and business process automation. • Experience implementing AI-assisted software testing frameworks. • Familiarity with hybrid deterministic + LLM-based decision systems.

Success Metrics • Reduction in manual processing for enrollment change requests. • Increased automation coverage beyond current rule-based capabilities. • Faster rule creation and deployment for new business scenarios. • Significant reduction in testing and development cycles through AI-generated test scenarios. • Improved handling of edge cases and previously unseen production exceptions. • Scalable deployment of Agentic AI solutions across 120+ business scenarios.

Pay: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not be

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