Guardian is undergoing a transformation to become a modern insurance company, and this role aims to leverage cutting-edge AI, specifically Agentic AI and LLMs, to automate business workflows, enhance decision-making, and deliver measurable business outcomes, thereby driving growth, improving risk management, and elevating customer experience.
Requirements
- 3+ years of hands-on experience in AI/ML modeling and development, with a primary focus on agentic AI, LLMs, and NLP.
- Deep expertise in LLMs, generative AI, agentic systems, NLP, and multi-step reasoning architectures (e.g., LangGraph, RAG, agent frameworks).
- Strong programming skills in Python and familiarity with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and LangChain.
- Demonstrated experience building, fine-tuning, and deploying LLMs and NLP solutions in production environments.
- Working knowledge of classical machine learning techniques (e.g., clustering, regression, XGBoost, Random Forest, decision trees) and their practical applications.
- Experience with data wrangling, distributed computing, and applying parallelism to ML solutions.
- Working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging, CI/CD).
Responsibilities
- Lead the design and implementation of agentic AI solutions and LLM-powered applications that automate business processes and improve customer and employee experiences.
- Drive the end-to-end model lifecycle: data exploration and preparation, model finetuning, validation, deployment, and monitoring, ensuring quality, security, scalability, and fairness.
- Apply LLMs and generative AI to process and interpret unstructured data (e.g., insurance applications, underwriter’s notes, medical records, customer interactions).
- Develop autonomous agents, multi-step reasoning systems, and advanced NLP pipelines that integrate with Guardian’s platforms.
- Translate research in agentic AI, LLMs, and reinforcement learning into practical, production-ready solutions for underwriting automation, claims automation, customer servicing, and risk assessment.
- Collaborate with data engineers, MLOps/AIOps, and product teams to ensure robust, scalable, and maintainable solutions.
- Contribute to standardization of tools, processes, and best practices.
Other
- PhD with 2+ years, Master’s with 4+ years of experience in Computer Science, Engineering, Statistics, Applied Mathematics, or related field.
- Experience in Insurance Underwriting
- Proven experience in providing technical leadership and mentoring to data scientists and strong project management skills with ability to monitor/track performance for enterprise success
- Excellent analytical, problem-solving, and communication skills.
- Experience in insurance, financial services, or related industries is a plus.
