Systems Engineer

Compunnel, Inc.; Austin (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

Compunnel, Inc. is looking for an experienced Systems Engineer to support large-scale technology transformations. The role focuses on modernizing enterprise systems and involves working with AI-assisted workflows and cloud-native applications. Ideal candidates have strong expertise in Java, DevOps practices, microservices, and AI/ML implementation. You will design and develop scalable systems while collaborating with cross-functional teams. Candidates should have significant professional experience in a fast-paced Agile environment.

Qualifications

• 7+ years of professional software engineering experience developing large-scale applications.
• 2+ years of hands-on experience with AI/ML implementation and production deployment.
• 6+ years of experience with containers and microservices in cloud environments.

Responsibilities

• Design, develop, and support large-scale enterprise applications.
• Lead and contribute to AI-assisted development workflows across the SDLC.
• Build and support cloud-native applications using microservices.

Skills

Java

Cloud technologies

Microservices

AI/ML implementation

DevOps practices

CI/CD

Containers

Agile methodologies

Education

Bachelor’s degree in Computer Science, Software Engineering, or a related technical field

Master’s degree in Information Technology, Computer Science, or related field

Tools

Pivotal Cloud Foundry (PCF)

AWS

GCP

MongoDB

Aerospike

PostgreSQL

GitHub Copilot

RabbitMQ

Kafka

JIRA

Confluence

Job description

We are seeking an experienced Systems Engineer to support large-scale technology transformation and modernization initiatives within enterprise systems and cloud environments. This role will focus on AI-assisted software development workflows, cloud-native application modernization, and scalable distributed systems. The ideal candidate will have strong expertise in Java, cloud technologies, microservices, AI/ML implementation, and DevOps practices, along with experience working in highly available enterprise environments.

Key Responsibilities

• Design, develop, and support large-scale enterprise applications and distributed systems
• Lead and contribute to AI-assisted development workflows across the Software Development Life Cycle (SDLC)
• Utilize Generative AI tools to support implementation, refactoring, testing, troubleshooting, automation, documentation, and code reviews
• Build and support cloud-native applications using microservices and containerized architectures
• Participate in system modernization initiatives including migration from legacy platforms to distributed cloud-based systems
• Develop and maintain CI/CD pipelines and automated deployment processes
• Collaborate with developers, architects, QA teams, and cross-functional stakeholders to deliver scalable and reliable solutions
• Work with databases and messaging technologies to support high-volume transactional systems
• Create and maintain technical documentation, architecture diagrams, and system specifications
• Support Agile development practices and continuous improvement initiatives

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience
• 7+ years of professional software engineering experience developing large-scale applications using Java, Spring Framework, cloud technologies, and web services
• 2+ years of hands‑on experience with AI/ML implementation and production deployment
6+ years of experience working with containers and microservices in cloud environments
• 6+ years of experience with CI/CD and cloud deployment practices
• 2+ years of experience with Pivotal Cloud Foundry (PCF), AWS, or GCP
• 2+ years of experience with databases such as MongoDB, Aerospike, or PostgreSQL
• Experience supporting modernization initiatives from legacy systems to distributed platforms
• Hands‑on experience with Large Language Models (LLMs) such as GPT, Claude, Gemini, or PaLM
• Practical experience using Generative AI coding assistants such as GitHub Copilot or Claude Code
• Understanding of AI-assisted development workflows, prompt engineering, and spec-driven development
• Strong understanding of microservices architecture and highly available systems
• Excellent communication, collaboration, and problem‑solving skills
• Ability to work effectively in fast‑paced Agile environments

Preferred Qualifications

• Master’s degree in Information Technology, Computer Science, or related field
• Knowledge of messaging technologies such as RabbitMQ or Kafka
• Experience working in the Financial Services industry
• Experience with Test Driven Development (TDD), QA automation, and quality engineering practices
• Experience creating architectural diagrams, technical documentation, and functional specifications
• Familiarity with Agile methodologies and Agile delivery environments
• Experience with Atlassian tools such as JIRA and Confluence
• Willingness to learn and support multiple areas of the technology stack