Top Tech Jobs & Startup Jobs

Design, build, and maintain solutions using Java and AWS, develop APIs, contribute to cloud migration, and uphold architectural standards within an agile team.

The AVP Applied AI leads data science and AI capabilities at The Hartford, managing complex AI portfolios and ensuring delivery of business value through scalable models and AI-driven systems. Responsibilities include overseeing team performance, technical direction, AI governance, and alignment with business outcomes, along with collaboration across departments and continuous improvement initiatives.

Lead planning, forecasting, and performance analysis for P&C lines; partner with finance, actuarial, and business leaders to provide insights, govern models, automate processes, and prepare executive reporting. Drive assumptions for loss ratios, catastrophes, reinsurance analyses, and earnings prep while mentoring a team and implementing analytics and AI-enabled improvements.

Lead and support the GAAP monthly financial close for Property & Casualty, perform reconciliations and variance analysis, produce segment financials, maintain allocations and TM1 reports, support SOX and audit readiness, and identify and implement process improvements and special projects.

Design, build, and deploy end-to-end AI/ML and generative solutions (RAG, chat/assistants, forecasting, recommendations). Engineer domain knowledge bases, handle unstructured data and OCR, implement evaluation/monitoring, ensure compliance and responsible AI, collaborate with stakeholders, and operationalize models in production across cloud platforms.

Design, build, and deploy production-grade AI/ML and agentic systems (multi-agent workflows, RAG, memory, evaluation-driven development). Collaborate with data science, platform, and cloud teams to implement scalable MLOps, observability, ETL pipelines, model serving, and CI/CD on AWS/GCP. Mentor junior engineers and contribute to SDKs, starter packs, and enterprise AI architecture and standards.

Design and deliver end-to-end AI/GenAI solutions (RAG, chat/agents, forecasting, recommendations); build domain knowledge bases and regulatory filing automation; manage unstructured data, retrieval, prompt/agent design, evaluation, monitoring, synthetic data, and MLOps integrations while ensuring compliance and stakeholder alignment.

Design and deliver end-to-end AI/ML and Generative AI solutions (RAG, chat/assistants, classification, forecasting, recommendations). Build domain knowledge bases, handle unstructured data/OCR, author prompts and agents, ensure responsible AI and compliance, operationalize models into production, monitor evaluation and drift, generate synthetic data, and collaborate with stakeholders and platform teams for scalable, secure deployments.

Design, build, and deploy end-to-end AI/ML and generative solutions (RAG, chat/assistants, classification, forecasting, recommendations). Engineer domain knowledge bases, ensure compliance and responsible AI, prepare unstructured data, design retrieval and prompt/agent systems, evaluate/monitor models, generate synthetic data, and partner across product, operations, and platform teams for scalable production integration.

Design, build, and deploy production-grade AI/ML and agentic systems (multi-agent workflows, RAG, evaluation, memory, prompt optimization). Collaborate with data science, platform, MLOps, and cloud teams to implement scalable, observable solutions and CI/CD, and mentor junior engineers.