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Design and implement AI-powered web and mobile features, integrating LLM agents into conversational UIs. Own full-stack work from Python/Postgres backend to React/React Native frontends, build real-time streaming chat experiences, and deliver product-quality 0-to-1 features that improve member experience and reduce healthcare friction.

Design and ship full‑stack, AI‑native insurance systems across underwriting, claims, operations, and member products. Build backend, frontend, AI workflows, retrieval/memory systems, and production infrastructure while owning features end-to-end and partnering closely with operational teams to reduce manual work and improve member experience.

Build and own AI-native, full-stack systems across underwriting, claims, operations, and member products. Ship end-to-end products using frontend, backend, and AI infrastructure, redesign workflows, automate manual operations, and collaborate directly with operational teams to scale insurance systems.

Build and own ML infrastructure for underwriting: scalable training on tens of millions of patients, low-latency real-time inference for quoting, and tooling for faster data-science iteration including backtesting, validation, and experiment infrastructure. Ensure reliability, monitoring, SLAs, and on-call operations while collaborating with data scientists and actuaries.

Lead end-to-end data and ML infrastructure powering underwriting and enterprise data ontology. Own ingestion, large-scale model training, low-latency inference, backtesting, monitoring, and API serving. Manage and technical-lead a data engineering and data science team, partner with actuarial and product teams, and improve iteration speed and data quality across healthcare claims use cases.

The Growth Marketing Lead will develop marketing strategies, run campaigns across various channels, analyze performance, and optimize messaging to generate leads and partnerships.

As a Product Engineer, you will create AI-powered features for web and mobile apps, working with full-stack implementations to enhance member experience in healthcare.

Partner with founders to lead cross-functional strategic projects, design and launch new functions (marketing, clinical, partnerships, captive insurance), recruit and scale teams, and operationalize prototypes into production to drive growth and efficiency.

Build and maintain ingestion pipelines and dbt transformations for heterogeneous healthcare data (claims, enrollment, TPA feeds). Implement orchestration (Dagster/Airflow), monitoring, and data-quality observability. Partner with data science to support feature pipelines and feedback loops, document data limitations, and resolve upstream issues to ensure trustworthy data for underwriting and pricing.

The Senior ML Infrastructure Engineer will own data infrastructure, maintaining pipelines for underwriting and claims, and partner with data scientists to implement business logic into production code.