Software Engineer, Data Infrastructure - AI Platform in Abbeyville, Colorado at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer, Data Infrastructure - AI Platform based in the United States.

This is a hands-on engineering role focused on building and operating critical data infrastructure within a highly regulated government cloud environment. You’ll work on the distributed serving layer that powers fast, reliable data access for mission-critical investigations. The role combines database performance optimization, pipeline reliability, production operations, and AI-assisted engineering workflows. You’ll have meaningful ownership over systems where reliability, compliance, and speed are essential. As a key member of a distributed engineering team, you’ll collaborate closely with data platform, product, and forward-deployed engineering teams. The environment rewards independent problem-solving, technical rigor, adaptability, and strong operational ownership. It’s an opportunity to deepen your distributed systems expertise while contributing to technology designed to support safer communities.

• Optimize distributed data infrastructure: Own performance tuning for the serving layer, using query profiling and AI-assisted tooling to identify and resolve performance bottlenecks before they affect customers.
• Build reliable data pipelines: Develop, maintain, and harden pipelines that support government cloud investigations, with a strong focus on reliability, correctness, and compliance.
• Strengthen operational resilience: Become a second independent owner of the serving infrastructure, reducing single points of failure and improving incident response capabilities.
• Troubleshoot production systems: Use AI-assisted debugging, log analysis, code exploration, and other engineering tools to investigate incidents and drive efficient root-cause resolution.
• Own production reliability: Participate in on-call responsibilities, respond to incidents, improve runbooks, and implement learnings from production retrospectives.
• Deliver infrastructure improvements quickly: Take ownership of infrastructure initiatives from investigation and design through implementation, testing, deployment, and ongoing operation.
• Support compliance requirements: Build and maintain infrastructure capabilities that meet evolving government cloud security, reliability, audit, and data-retention requirements.
• Collaborate across engineering and product: Work closely with Data Platform, Forward Deployed Engineering, Product, and other teams to maintain reliable and consistent capabilities across government and commercial environments.
• Use AI as an engineering multiplier: Apply AI tools to accelerate debugging, code reviews, documentation, configuration work, research, and other repeatable engineering workflows while maintaining high technical standards.
• Contribute to technical decision-making: Make architecture and infrastructure trade-offs based on evidence, operational experience, and system requirements, while sharing knowledge with the broader engineering organization.

• U.S. citizenship is required due to government cloud data access requirements.
• Hands-on experience operating distributed OLAP, analytical databases, or serving-layer systems such as StarRocks, Trino, ClickHouse, or comparable technologies.
• Strong experience with query tuning, database performance optimization, and distributed systems at scale.
• Experience owning data pipeline reliability, production operations, and incident response.
• Demonstrated ability to independently learn and operate unfamiliar production infrastructure with minimal oversight.
• Comfort with on-call responsibilities, production troubleshooting, and working in environments where reliability and operational excellence are critical.
• Strong practical experience using AI-powered engineering tools such as Claude, Cursor, or comparable solutions to accelerate debugging, code review, research, documentation, and development.
• Ability to apply AI thoughtfully to improve engineering speed and output quality rather than simply automate routine tasks.
• Strong ownership mindset, with the ability to identify problems proactively and drive solutions from discovery through production.
• Excellent technical judgment, communication, and collaboration skills.
• Comfort working in a fast-paced, high-ownership environment with evolving priorities and a degree of ambiguity.
• Ability to balance urgency and delivery speed with security, reliability, compliance, and high engineering standards.

• Fully remote position for eligible US-based employees.
• Opportunity to work on complex data infrastructure at the intersection of AI, public safety, security, and mission-critical technology.
• High-autonomy environment with significant ownership over architecture, infrastructure, and operational outcomes.
• Exposure to advanced distributed data systems, AI-assisted engineering practices, and highly regulated cloud environments.
• Collaborative, distributed-first culture with frequent communication and cross-functional partnership.
• Opportunity to participate in meaningful infrastructure projects with tangible customer and societal impact.
• Fast-paced environment that emphasizes learning, experimentation, technical craftsmanship, and career growth.
• Work alongside experienced engineers and cross-functional teams tackling complex technical and operational challenges.