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Compunnel, Inc.
Senior Gen-AI Software Engineer
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$132,765 / year median in Texas
Job Description
Job Summary We are seeking a Senior GenAI Software Engineer to lead AI-driven software development initiatives and modernize enterprise applications. This role combines deep software engineering expertise with hands-on experience building and integrating Generative AI solutions to accelerate the Software Development Life Cycle (SDLC). The ideal candidate will develop intelligent systems, implement AI-assisted engineering workflows, and contribute to large-scale modernization initiatives in a highly available cloud environment. Key Responsibilities
- Design, develop, and maintain enterprise applications using modern software engineering practices.
- Lead AI-assisted development initiatives across the Software Development Life Cycle (SDLC).
- Build and integrate custom AI agents and AI-powered development tools to improve engineering productivity.
- Leverage Generative AI coding assistants for implementation, refactoring, code reviews, testing, troubleshooting, scripting, automation, and documentation.
- Establish best practices for AI-assisted software development, prompt engineering, and agentic workflows.
- Translate technical designs, API contracts, and data models into structured specifications for AI-assisted implementation.
- Develop scalable microservices and cloud-native applications using Java, Spring Framework, and modern cloud technologies.
- Participate in enterprise application modernization and migration from legacy platforms to distributed architectures.
- Design, develop, and deploy AI/ML solutions into production environments.
- Collaborate with developers, architects, product teams, and business stakeholders to deliver high-quality solutions.
- Contribute to CI/CD pipelines, automated testing, and continuous improvement initiatives.
- Create and maintain technical documentation, architectural diagrams, and design specifications.
- Mentor engineering teams on AI-assisted development practices and software engineering best practices. 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 enterprise applications.
- Strong experience with Java and Spring Framework.
- Experience developing cloud-native applications and web services supporting high-volume, highly available systems.
- 6+ years of experience with containers, microservices, and cloud-based application development.
- 6+ years of experience implementing CI/CD pipelines and cloud deployment practices.
- 2+ years of hands-on experience developing and deploying AI/ML solutions in production.
- 2+ years of experience with AWS, Google Cloud Platform (GCP), or Pivotal Cloud Foundry (PCF).
- 2+ years of experience working with MongoDB, Aerospike, PostgreSQL, or similar databases.
- 2+ years of experience supporting enterprise modernization initiatives involving legacy-to-distributed system migrations.
- Hands-on experience with Large Language Models (LLMs) such as GPT, Claude, Gemini, or PaLM.
- Experience using Generative AI coding assistants such as GitHub Copilot or Claude Code throughout the SDLC.
- Experience implementing AI-assisted workflows, prompt engineering, custom instructions, and agentic development practices.
- Strong understanding of software engineering principles, distributed systems, APIs, and microservices architecture.
- Excellent communication, collaboration, leadership, and problem-solving skills.
- Ability to work effectively with cross-functional engineering and architecture teams. Preferred Qualifications
- Master's degree in Computer Science, Information Technology, or a related field.
- Experience developing custom AI agents and AI-powered engineering tools.
- Background in .NET software engineering.
- Experience with messaging technologies such as RabbitMQ or Kafka.
- Experience in the financial services industry.
- Experience with Test-Driven Development (TDD), QA automation, and software quality practices.
- Experience creating architectural diagrams, technical documentation, and functional specifications.
- Experience documenting production environments and solution architectures.
- Knowledge of Agile development methodologies.
- Experience with Jira and Confluence.