Java Full stack Developer

Virtusa • Tampa, FL

14d

About The Position

We are seeking a highly experienced Java Full Stack Developer with a strong background in Python or Java and proven experience in designing and delivering Large Language Model (LLM) / Generative AI (GenAI) solutions. The ideal candidate will have a solid understanding of microservices, APIs, distributed systems, and enterprise integration patterns, along with experience in reviewing and governing AI-assisted code. A strong foundation in secure coding practices and performance optimization is essential. This role involves designing and implementing LLM-based solutions, understanding model lifecycles, inference pipelines, performance tuning, and cost optimization. Familiarity with AI governance concepts, cloud-native or hybrid environments, containers, orchestration platforms, CI/CD pipelines, observability, and production support models is also required. Knowledge of secure coding practices and enterprise security standards is crucial.

Requirements

• Strong hands-on experience (10-12 years) in Python or Java (mandatory).
• Proven experience designing and delivering LLM / GenAI solutions (e.g., RAG, orchestration, prompt engineering, AI-assisted automation).
• Solid understanding of microservices, APIs, distributed systems, and enterprise integration patterns.
• Experience reviewing and governing AI-assisted / GenAI-generated code.
• Strong foundation in secure coding practices and performance optimization.
• Experience designing and implementing LLM-based solutions (RAG, agents, copilots, automation).
• Understanding of model lifecycle, inference pipelines, performance tuning, and cost optimization.
• Familiarity with AI governance concepts such as bias, explainability, auditability, and model risk controls.
• Experience with cloud-native or hybrid environments, containers, and orchestration platforms.
• Exposure to CI/CD pipelines, observability, and production support models.
• Knowledge of secure coding practices and enterprise security standards.

Responsibilities

• Design and deliver LLM / GenAI solutions (e.g., RAG, orchestration, prompt engineering, AI-assisted automation).
• Review and govern AI-assisted / GenAI-generated code.
• Implement secure coding practices and performance optimization.
• Design and implement LLM-based solutions (RAG, agents, copilots, automation).
• Understand model lifecycle, inference pipelines, performance tuning, and cost optimization.
• Apply AI governance concepts such as bias, explainability, auditability, and model risk controls.
• Work with cloud-native or hybrid environments, containers, and orchestration platforms.
• Utilize CI/CD pipelines, observability, and production support models.
• Adhere to secure coding practices and enterprise security standards.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed