Jobgether

Software Engineer, Data Infrastructure - AI Platform

Jobgether United States

Internet Marketplace Platforms · 11-50 employees

14 h ago
Remote Senior (5-10 yrs) Full-time United States
Log in to apply, save this posting, or score it against your profile with AI.

About the role

You will own the performance tuning and reliability of distributed data infrastructure within a government cloud environment. This involves building robust data pipelines, managing production incidents, and leveraging AI tools to accelerate engineering workflows.

What they look for

Distributed systems Data infrastructure Database performance optimization Query tuning OLAP StarRocks Trino ClickHouse Data pipelines Production operations Incident response AI-powered engineering tools Claude Cursor Cloud security System architecture

Requirements

U.S. citizenship is required due to government cloud data access mandates. Candidates must have hands-on experience with distributed OLAP systems, database performance tuning, and production-level incident response.

Benefits

Fully remote position High-autonomy environment Exposure to advanced distributed data systems AI-assisted engineering practices Collaborative culture Meaningful infrastructure projects Career growth opportunities

Full description

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.

\n

Accountabilities

  • 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.

Requirements

  • 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.

Benefits

  • 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.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1