Senior Gen-AI Software Engineer

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.