
Lead, Data AI – Engineering
Posted 16 hours ago

Posted 16 hours ago
This is a fully remote position, open to applicants in Minnesota.
• Design and develop MHC’s foundational data platform encompassing ingestion, transformation, storage, and serving layers for both batch and streaming workloads.
• Structure data for analytics and product applications, generating well-documented reusable datasets and a reliable semantic layer.
• Implement practices for data quality, lineage, observability, and governance.
• Create pipelines and feature/embedding stores to support analytics, machine learning, and LLM applications.
• Convert operational and document data into metrics, signals, predictions, and document comprehension.
• Develop and assess models and retrieval systems, including RAG for document handling.
• Collaborate with Product teams to design and deploy LLM-driven features from concept to production with safeguards, evaluation mechanisms, and cost management.
• Lead, mentor, and expand a team of 2–4 data and AI engineers.
• Define technical standards and establish a practical data and AI roadmap.
• Make decisions regarding build-vs-buy options while balancing speed and maintainability.
• Work alongside Product, Engineering, and business stakeholders.
• Review code and designs, prototype complex challenges, and uphold engineering quality.
• Deliver a prioritized roadmap and achieve initial data-layer successes within 90 days.
• Create a robust data foundation and launch the first AI/LLM-powered feature within six months.
• Develop a continuous flow of data products and AI features over the span of a year.
• Bachelor’s degree in Computer Science, Information Security, or a related discipline, or equivalent experience.
• Over 7 years of experience in building data and/or backend systems in production, including recent hands-on work in data engineering and applied AI/ML.
• Proficient in SQL and Python.
• Familiarity with cloud warehouse/lakehouse solutions such as Snowflake, BigQuery, Databricks, or Redshift.
• Experience with data transformation tools like dbt.
• Knowledge of orchestration tools such as Airflow, Dagster, or Prefect.
• Direct experience in developing production AI/ML features.
• Practical understanding of LLMs, including prompting, RAG, embeddings/vector search, evaluation, and model integration via APIs or open-source models.
• Solid software engineering principles encompassing data modeling, API design, testing, CI/CD, and dependable systems on AWS, GCP, or Azure.
• Experience in leading or mentoring engineers with a desire to grow a team.
• Strong product intuition and communication abilities.
• Preferred: experience in document AI/intelligent document processing or NLP for unstructured text.
• Preferred: operational experience with LLMs in production, including evaluation/observability, prompt and cost optimization, fine-tuning, or agentic workflows.
• Preferred: background in B2B SaaS, document/process automation, fintech, or other data-oriented enterprise sectors.
• Preferred: knowledge of data privacy, security, and compliance standards such as SOC 2 and GDPR.
• Preferred: experience with streaming, infrastructure-as-code, and MLOps/LLMOps tools.
• Candidates must reside in the United States.
• This position does not qualify for visa sponsorship.
• Flexible work-from-anywhere model.
• 401(k) plan with both deferred and Roth options, including an employer match of 50% up to a maximum of 4.5% of gross pay.
• Comprehensive medical plans with co-pay or HSA coverage options.
• Dental and vision insurance.
• Daycare and Medical FSA/HSA options.
• Group term life insurance coverage of $50,000.
• Generous paid time off (PTO) policies.
• Employee Assistance Program (EAP).
• Additional life insurance options.
• Critical illness coverage.
• Accident, cancer, and hospital indemnity insurance.
• Legal/ID Shield services.
• Pet insurance.
• Four weeks of paid paternity leave after one year of employment, with partial eligibility starting at six months where no state paid leave program is applicable.
• Twelve weeks of paid leave for the birth parent, subject to eligibility rules.
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