• They are comfortable operating without full clarity.
• They pay attention to what actually happens, not just what was intended.
• They are willing to be wrong, adjust quickly, and improve based on real feedback.
• They take responsibility for outcomes, not just implementation.

• Competitive base salary
• Quarterly performance bonuses
• Equity participation within the first 12 months
• Unlimited PTO + 11 paid company holidays
• Professional development in a high-growth, mission-driven environment
• Weekly in-office catering at HQ

• 401(k) plan (no current employer match, but under consideration)
• PPO, HSA, and TRICARE Supplement medical options
• Above-market HSA contributions
• HSA, FSA, and Dependent Care FSA options
• Dental and vision plans above national averages
• Employer-paid life insurance (1× salary)
• Employer-paid Short-Term and Long-Term Disability
• Voluntary Accident, Critical Illness, and Hospital Indemnity coverage
• Up to $300/month in tax-advantaged commuter benefits

Role Overview

• Design, build, and maintain backend services and pipelines that acquire and process data from diverse data sources, including:
  • Extensible connector and adapter patterns so new data sources, workflows, and processing methods can be added without rebuilding the core platform.
  • Systems that monitor and respond to real-world events by collecting, correlating, and updating relevant data streams.
  • Data transformation, enrichment, and normalization processes to support downstream analytics and mission applications.
• Build and implement workflows that:
  • Allow users to configure, run, review, and manage data processing tasks through controlled application interfaces.
  • Support human-in-the-loop review and promotion workflows so raw or enriched data can be validated before becoming available to downstream users or systems.
  • Incorporate automated data access workflows using APIs, web interfaces, and distributed systems while adhering to controlled access and usage constraints.
  • Optimize performance, scalability, and resilience of data acquisition and processing systems.
• Partner with AI/ML engineers to:
  • Integrate data fusion capabilities that combine multiple sources to improve data completeness, context, and usability.
  • Integrate AI-enabled capabilities into data workflows, including structured extraction, classification, summarization, validation, and routing through approved internal services.
• Partner with security engineers to:
  • Implement policy enforcement, fail-closed validation, audit evidence, and infrastructure safeguards for sensitive data workflows.
  • Implement safeguards that reduce attribution risk and ensure responsible interaction with external data sources.
  • Apply operational security practices to data acquisition and processing workflows, including controlled access patterns, traffic shaping, and protection of system and infrastructure.
  • Ensure systems meet compliance, auditability, and mission requirements.
• Contribute to CI/CD pipelines, containerized deployments, and automated testing workflows.
• Troubleshoot production issues and perform root-cause analysis across distributed systems.
• Document system behavior, data flows, and integration patterns to support maintainability and operational use.
• Participate in code reviews and contribute to engineering standards and best practices.

• B.S. or M.S. in Computer Science, Engineering, or related field.
• 3–6 years of professional software engineering experience.
• Strong proficiency in Python (preferred) or similar backend programming languages.
• Strong understanding of data pipeline patterns, including ETL/ELT workflows.
• Experience building production systems for data ingestion, integration, or processing.
• Experience working with APIs, automated data access techniques, and distributed systems.
• Experience working with structured and semi-structured data formats (JSON, CSV, Parquet).
• Experience designing systems that operate reliably under variable data availability and latency conditions.
• Experience with CI/CD pipelines and modern software development practices.
• Experience implementing controlled or privacy-aware data acquisition techniques, such as controlled access, managed attribution, fail-closed validation, etc.
• Familiarity with SQL and NoSQL databases and query optimization.
• Familiarity with cloud environments (AWS preferred) and containerization (Docker).
• Understanding of secure software development practices and controlled data access patterns.
• Strong problem-solving skills and ability to operate in fast-paced, mission-driven environments.

• Experience with workflow orchestration tools (Airflow, NiFi) or similar systems.
• Experience with streaming or event-driven architectures (Kafka or equivalent).
• Experience working with geospatial, temporal, or multi-source datasets.
• Experience supporting defense, intelligence, or other regulated environments.
• Familiarity with large-scale data ingestion, indexing, or search systems.
• Familiarity with infrastructure patterns that support identity protection, request management, or traffic routing in distributed systems.
• Familiarity with distributed systems and microservices architectures.
• Exposure to observability tooling (logging, monitoring, metrics).
• Exposure to data enrichment, entity resolution, or relationship mapping techniques.