Intern, Risk Intelligence Engineer

The Hartford • Hartford, CT

2d

About The Position

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. At The Hartford, the Y-Risk Innovation Lab is dedicated to leveraging tomorrow’s emerging technologies to better understand, quantify, and mitigate complex risks. The Risk Intelligence team operates as a highly nimble, "skunkworks" R&D unit within the lab. In this group, we focus on the intersection of physical AI and digital AI for assessing and mitigating risk exposures. This role operates within a broader Risk Intelligence portfolio and collaborates closely with other applied researchers and partners. We are seeking a multidisciplinary Risk Intelligence Engineer to join this fast-paced, experimental effort. Rather than maintaining legacy systems, this role is about building the future of risk modeling and loss prevention through rigorous applied research. The ideal candidate operates effortlessly across three core pillars: 1) Artificial Intelligence, 2) Physical Engineering, and 3) Risk Assessment. You will apply advanced robotics technologies (e.g., Boston Dynamics Spot) and cutting-edge machine learning to actively identify, assess, and mitigate real-world risk exposures. By seamlessly transitioning between complex data wrangling, physical robotics, and digital AI development, you will help pioneer our approach to Agentic AI and Risk Engineering. Drawing on your deep understanding of how physical systems operate and fail, you will develop predictive risk models and deploy autonomous agents to uncover hidden exposures in complex environments.

Requirements

• Education: Master’s degree (or equivalent experience) in Engineering, Data Science, Robotics, or a related field. Bachelor’s degree in Engineering Sciences, Electrical Engineering, or similar.
• The Three Pillars (AI, Engineering, Risk): Proven ability to bridge the gap between complex physical engineering concepts, advanced data science/AI, and real-world risk mitigation.
• Robotics & Application: Proven academic or industry experience in the modeling, simulation, and physical actuation of complex systems.
• AI/ML Expertise: Strong understanding of machine learning architectures with a demonstrated ability to employ state-of-the-art, foundational multi-modal LLMs to solve practical business problems and improve predictive modeling.
• Risk Modeling & Physical Exposures: Experience translating complex physical data (e.g., structural analysis, fluid dynamics, hardware testing) into predictive models or algorithms that identify, quantify, and predict real-world exposures or system failures.
• Programming & Data: High proficiency in Python for heavy data wrangling and algorithmic development, with additional experience in engineering software to bridge the physical-to-digital gap.

Nice To Haves

• Understanding of cloud architecture (AWS/GCP) and the ability to navigate, build, and deploy solutions within modern cloud environments.
• Strong foundational logic in complex physical systems, with a high aptitude and willingness to learn agentic coding and autonomous agent deployment.
• Entrepreneurial mindset with the ability to act as a collaborative problem-solver within a stealthy, fast-paced "skunkworks" innovation lab.

Responsibilities

• Agentic Risk Engineering & Risk Assessment: Leverage your foundation in physical engineering and systems testing to pioneer the application of Agentic AI within a large-scale insurance context. With on-the-job training in agentic coding frameworks, you will design simulation environments and deploy AI-driven agents to evaluate complex scenarios, identify hidden policyholder exposures, and automate proactive risk assessment.
• Mobile & Advanced Robotics (e.g., Spot): Act as the technical point person for the applied use of physical AI platforms (such as Boston Dynamics Spot). Apply advanced robotics technologies to real-world risk scenarios, utilizing deep engineering principles to optimize robotic navigation, sensor deployment, and automated site inspections.
• Applied AI & Multi-Modal LLMs: Leverage a deep understanding of complex neural network topologies to employ state-of-the-art, foundational multi-modal LLMs. Apply these advanced models to map complex physical environments, analyze imagery, and solve critical business and predictive risk problems.
• Complex Data Wrangling & Imagery Analysis: Ingest, clean, and process massive amounts of unstructured data, including novel third-party datasets, policyholder data, and high-resolution imagery (aerial, drone, and on-the-ground risk engineering captures). Utilize Python and advanced data analysis techniques to extract actionable risk intelligence from complex visual and physical data.
• Applied Research & Scientific Rigor: Apply a formal scientific method to our skunkworks R&D initiatives. Move systematically from hypothesis generation and experimentation to rigorous validation and signal strength assessment. Ensure that our bleeding-edge innovations are empirically sound and built for real-world deployment, effectively filtering out "demo-only" builds.
• Business Translation & Rapid Prototyping: Act as a catalyst for innovation by rapidly prototyping new, home-grown risk models. Leverage your deep understanding of structural engineering, fluid dynamics, and physical systems to translate complex physical exposures into intuitive digital tools. Partner directly with Underwriters and Risk Engineers to bridge the gap between technical insight and business action, directly influencing critical decision points around risk eligibility, pricing, and proactive mitigation.

What This Job Offers

• Career Level: Intern
• Number of Employees: 5,001-10,000 employees