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Java Full stack Developer

  • Job type Posted on: Jul 13, 2026
  • Experience level Virtusa
  • Employment type Tampa, Florida
  • Employment type Onsite
  • Salary Full-time

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Job Title :

Java Full stack Developer

Job Type :

Full-time

Job Location :

Tampa Florida United States

Remote :

No

Jobcon Logo Job Description :

Java Full stack Developer (CREQ263104) 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 insecure coding practices and performance optimization. AI & GenAI 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. #J-18808-Ljbffr

Jobcon Logo Position Details

Posted:

Jul 13, 2026

Reference Number:

14660_E6D44E2DD08A883E6154FE114B1F0A00

Employment:

Full-time

Salary:

Not Available

City:

Tampa

Job Origin:

APPCAST_CPC

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Java Full stack Developer (CREQ263104) 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 insecure coding practices and performance optimization. AI & GenAI 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. #J-18808-Ljbffr

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