Senior Software Engineer

You'll build the data and retrieval foundation that makes Clearwater's AI agents accurate, grounded, and measurable. This is a hands-on software engineering role, not a research role: you'll write production pipelines and services, build retrieval and evaluation systems, and ship the product surfaces that expose them. You'll work across security and threat data at scale.

• Build and operate data pipelines (batch and streaming) that ingest, normalize, and enrich large volumes of security and telemetry data
• Design retrieval systems for agents: chunking, embeddings, hybrid search, reranking, vector and graph stores, and freshness and access control
• Build evaluation harnesses and datasets to measure agent and retrieval quality, regressions, and cost
• Build backend APIs and services in Python, and the full-stack features that surface data and AI insights to users
• Design data models and manage relational, analytical, and vector stores for performance and cost
• Add data quality checks, lineage, observability, and governance, including PII and sensitive-data handling
• Use AI agents to automate data engineering work such as pipeline generation, data validation, and documentation
• Containerize and deploy on Kubernetes and cloud with CI/CD, and mentor engineers on data and AI practices

• 4+ years of professional software engineering with strong data-engineering exposure and sound testing and CI/CD practice
• 1+ year building production systems involving LLMs, retrieval (RAG), or large-scale data pipelines
• Strong Python and SQL, including query optimization and data modeling
• Hands-on with pipeline or stream-processing tooling such as Airflow, Dagster, Spark, or Kafka, or an equivalent
• Experience with vector stores and retrieval design (pgvector, OpenSearch, or similar), and with evaluating retrieval quality
• Docker, working Kubernetes knowledge, and experience on AWS, Azure, or GCP

• Working JavaScript/TypeScript, enough to build and ship full-stack features
• Experience with security, threat intelligence, or SIEM/telemetry data
• Healthcare or compliance-driven data experience (HIPAA, SOC 2, HITRUST)
• Knowledge graphs or graph databases
• LLMOps and evaluation tooling experience
• Experience with a lakehouse or warehouse such as Snowflake, Databricks, or BigQuery
• Open-source contributions or public data or retrieval projects

Experience: 4+ years in software engineering, including 1+ year building data-intensive or LLM-powered systems in production

• Ship production pipelines and retrieval services with clear quality and reliability targets
• Deliver a retrieval and evaluation framework that measurably improves agent accuracy
• Establish the team's patterns for data quality, grounding, and sensitive-data handling

You'll have high ownership at an early-stage engineering site, direct exposure to leadership, and the chance to build the data foundation behind AI-driven security products that protect healthcare organizations.

Disclaimer: The above statements are intended to describe the general nature and level of work being performed by people assigned to this position. They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of colleagues in the role. All colleagues may be required to perform duties outside of their normal responsibilities from time to time, as needed.

Mental/Physical Requirements: Fast paced environment handling multiple demands. Must be able to exercise appropriate judgment as necessary. Requires a high level of initiative and independence. Excellent written and oral communication skills required. Requires the ability to use a personal computer for extended periods of time.