Senior Forward Deployed Data Engineer (AI)

Location: US Remote; other location: US - TX

Salary: USD 125,000–156,300 per year

Company

hirify.global develops cell-free DNA testing and personalized genetic testing products for oncology, women’s health, and organ health.

What you will do

• Partner directly with business stakeholders and domain teams as the primary technical advisor and builder for analytics and AI initiatives.
• Design, build, and operate scalable data pipelines and transformations using clinical, laboratory, operational, and commercial data.
• Develop governed analytical data models and semantic layers for self-service analytics, dashboards, and data products such as Patient 360, Provider 360, and Test 360.
• Build agentic workflows, retrieval-augmented generation, and LLM pipelines for extraction, classification, productivity, and automation.
• Implement data quality checks, contracts, lineage, monitoring, SLAs, incident response, and cost-efficiency improvements.
• Collaborate with platform and AI teams, participate in architecture and governance forums, and communicate technical tradeoffs to non-technical partners.

Requirements

• 7+ years of data or software engineering experience, including forward-deployed or customer-facing engineering roles delivering analytics and AI solutions directly to stakeholders.
• Ability to partner with non-technical business stakeholders, explain technical concepts clearly, and manage project deliverables.
• Hands-on daily use of AI coding assistants and agentic tools, with a clear approach to applying them effectively.
• Expert-level SQL and strong Python, with experience shipping and operating production data pipelines and data models at scale.
• Deep experience with a modern cloud data warehouse and cloud infrastructure; Snowflake and AWS are preferred.
• Hands-on experience with dbt or an equivalent transformation framework and Airflow, Dagster, Prefect, or a similar orchestration tool.
• 1–2 years of practical experience building with LangChain, LangGraph, or equivalent LLM frameworks, alongside managed AI services and model routing gateways such as Snowflake Cortex, AWS Bedrock, and foundational APIs.
• Strong grounding in analytical data modeling, semantic layers, data quality engineering, and CI/CD for data systems.
• Pipelines handling PHI and genomic data must meet HIPAA, CLIA, internal security, governance, access-control, auditability, and retention requirements.

Nice to have

• Experience in healthcare, life sciences, or another regulated domain handling PHI or sensitive data.
• Experience with lab data management, laboratory informatics, bioinformatics pipelines, Salesforce, laboratory information systems, or EHR data sources.
• Snowflake performance tuning, cost management, dynamic tables, Snowpark, or Cortex experience.
• Sigma or comparable BI and semantic-layer tools such as Looker, Tableau, or Power BI; Power BI dataset design, connectivity, and dashboard troubleshooting are useful.
• Experience operating agentic or LLM-based workflows in the data development lifecycle, infrastructure-as-code with Terraform, and data observability tooling.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.

Culture & Benefits

• Fully remote role within the United States, with a senior individual-contributor scope and direct collaboration with the Data & AI Engineering Tech Lead.
• Medical, dental, vision, life, and disability plans for eligible employees and dependents.
• Free testing for employees and immediate family members, plus fertility care benefits.
• Pregnancy and baby bonding leave, 401(k) benefits, commuter benefits, and an employee referral program.
• Work in a regulated environment where data quality, lineage, privacy, security, and reliable production delivery are essential.