AI Analytics Technical Lead

Location: Remote, hybrid, or on-site; proximity to a major hirify.global facility is required because periodic on-site collaboration is expected. U.S. citizenship is required.

Salary: USD $183,371–$203,428 per year

Company

hirify.global engineers high-technology solutions, products, and services for defense, scientific, and mission-critical applications.

What you will do

• Translate AI investment and operational needs into requirements, integration architecture, interfaces, acceptance criteria, and technical roadmaps.
• Connect approved telemetry, usage, capacity, cloud billing, application, identity, organizational, program, and financial-reference data through governed interfaces.
• Design and implement versioned data and telemetry contracts, stable identifiers, transformations, fact models, lineage, and reproducible reporting.
• Build quality controls, reconciliation, replay, recovery, monitoring, rollback criteria, and operational readiness evidence.
• Establish a governed reporting path across dashboards, reports, extracts, alerts, emails, and interfaces.
• Lead engineers, source owners, enterprise data teams, platform teams, security, privacy, Finance, and metric owners through matrixed delivery.

Requirements

• Bachelor’s degree in a relevant technical discipline with at least 10 years of relevant experience, or a master’s degree with at least 8 years of relevant experience.
• Experience as a technical lead or principal engineer for production analytics, telemetry, data integration, or Financial Operations capabilities.
• Strong SQL and Python skills, including governed transformations, analytical fact models, data-quality controls, and reporting pipelines.
• Experience with data contracts, APIs, idempotent processing, replay, reconciliation, schema evolution, observability, recovery, and controlled cutover.
• Experience with semantic and ontology mappings, effective-dated dimensions, lineage, metric versioning, privacy controls, and reproducible reporting.
• Ability to obtain a Department of Defense Secret security clearance and U.S. citizenship are required.

Nice to have

• Defense and aerospace experience, including controlled unclassified information and classified-environment data handling.
• Experience with AI or machine-learning platform operations, model-serving infrastructure, or large language model deployment.
• Experience with Snowflake, Azure, Databricks, PostgreSQL, lakehouse and event-driven patterns, Denodo, Power BI, CI/CD, data observability, and performance testing.
• Experience with cloud-consumption analytics, agent attribution, anomaly detection, forecasting, or scenario modeling.

Culture & Benefits

• Research-oriented work alongside teams developing practical solutions for national security.
• Flexible schedules, including an optional 9/80 schedule with every other Friday off.
• Competitive benefits including 401(k) matching, flexible time off, paid parental leave, healthcare, and wellness programs.
• Opportunities for continuous learning and professional development.