Senior Software Engineer

seekr; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

seekr in the United States seeks an experienced engineer to build and operate production software for federal AI applications, spanning commercial cloud to air-gapped environments. The role focuses on turning prototypes into secure, scalable services that meet accreditation requirements and function in limited-access settings.

You will partner with AI engineers, design secure distributed systems, maintain hardened containers and CI/CD pipelines, and mentor teammates through reviews and pairing.

Qualifications

• At least three years of professional experience building and operating large-scale distributed software systems.
• Bachelor’s degree in computer science or a related field, or equivalent professional experience.
• Active U.S. Top Secret security clearance.
• Production ownership and practical experience with Python, relational databases such as PostgreSQL, and REST API design; FastAPI is preferred.
• Experience with Docker, Kubernetes, Helm, CI/CD, automated testing, and observability; GitLab CI is preferred.
• Strong understanding of distributed systems concepts such as retries, idempotency, queueing, failure isolation, and graceful degradation, plus clear written and verbal communication.

Responsibilities

• Partner with AI engineers to deliver production-ready features and take services from prototype through deployment and accreditation.
• Design and operate distributed systems with security controls built into the architecture and delivery process.
• Build and maintain hardened container images, CI/CD pipelines, and deployment artifacts for cloud and air-gapped environments.
• Investigate production issues and identify root causes using available logs and diagnostics, including when systems cannot be reproduced locally.
• Break product requirements into actionable engineering work and contribute to technical decisions and team practices.
• Mentor colleagues through code, design reviews, and pairing.

Skills

Python

REST API design

Distributed systems concepts

CI/CD

Observability

Mentoring/leadership

Education

Bachelor’s degree in computer science or related field

Tools

Docker

Kubernetes

Helm

GitLab CI

PostgreSQL

FastAPI

Job description

Role overview

Build and operate production software for federal AI applications deployed across environments ranging from commercial cloud to government cloud and disconnected networks. The work focuses on turning prototypes into secure, reliable, scalable services that can meet accreditation requirements and function in settings with limited access and observability.

Responsibilities

• Partner with AI engineers to deliver production-ready features and take services from prototype through deployment and accreditation.


• Design and operate distributed systems with security controls built into the architecture and delivery process.


• Build and maintain hardened container images, CI/CD pipelines, and deployment artifacts for cloud and air-gapped environments.


• Investigate production issues and identify root causes using available logs and diagnostics, including when systems cannot be reproduced locally.


• Break product requirements into actionable engineering work and contribute to technical decisions and team practices.


• Mentor colleagues through code, design reviews, and pairing.

Requirements

• At least three years of professional experience building and operating large-scale distributed software systems.


• Bachelor’s degree in computer science or a related field, or equivalent professional experience.


• Active U.S. Top Secret security clearance.


• Production ownership and practical experience with Python, relational databases such as PostgreSQL, and REST API design; FastAPI is preferred.


• Experience with Docker, Kubernetes, Helm, CI/CD, automated testing, and observability; GitLab CI is preferred.


• Strong understanding of distributed systems concepts such as retries, idempotency, queueing, failure isolation, and graceful degradation, plus clear written and verbal communication.

Nice to have

• Experience shipping AI-backed features such as LLM inference, agents, or retrieval, with sound judgment about where those approaches fit. Familiarity with AI coding assistants is useful; the role expects engineers to review and take responsibility for shipped code.