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.