Generative AI engineer - Java full stack - Vice president

Senior Java Fullstack GenAI Developer - Vice President is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.

• About the Role:

  We are seeking a highly experienced and innovative Senior Generative AI Engineer with over 12 years of industry experience, including a strong background in Java Full-stack development, to join our dynamic team. The ideal candidate will be instrumental in designing, developing, and deploying cutting-edge generative AI solutions that drive significant business impact. This role requires deep hands-on expertise in building scalable enterprise-grade AI systems, coupled with a solid understanding of software development best practices and robust architecture patterns, with a proven track record in both Java and Python ecosystems.

  Responsibilities:

• Lead the engineering and execution of scalable enterprise Generative AI solutions from concept to production.
• Design, develop, and implement advanced AI models and systems, with a focus on generative AI, leveraging large language models (LLMs) and agentic AI architectures.
• Integrate AI services into existing enterprise systems by designing and implementing robust, high-performance APIs.
• Apply expert-level proficiency in Python frameworks (e.g., FastAPI, Django, Flask, PySpark) for AI development and system integration.
• Leverage significant past experience in Java development for building robust, scalable enterprise applications and integrating AI components within existing Java-based systems.
• Utilize deep understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems, to inform solution design.
• Gain hands-on experience with relevant AI frameworks and orchestration tools such as Google ADK, LangGraph, LangChain, AutoGen, and CrewAI.
• Leverage extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., Scikit-Learn, NumPy, Pandas) to build and optimize AI models.
• Develop, deploy, and integrate Model Context Protocols (MCPs) into sophisticated agentic AI systems.
• Demonstrate deep familiarity and practical application of large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama within agentic systems.
• Champion software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and rigorous code reviews.
• Ensure application resiliency and adhere to strong security principles in all AI projects.
• Apply expertise in system design, application development, and operational stability for critical AI initiatives.
• Utilize deep experience with application and data architecture patterns and designs, emphasizing API-First Design, microservices, and event-driven architectures.
• Leverage managed services and existing platforms effectively to accelerate development and deployment.
• Possess hands-on experience with containerization and orchestration technologies, specifically Docker and Kubernetes.
• Proactively identify and solve complex technical challenges with excellent analytical, innovative, pragmatic, and creative problem-solving skills.
• Qualifications:
• 12+ years of progressive experience in software engineering, with a significant focus on Generative AI.
• Prior hands-on experience in Java Full-stack development is required.
• Expert-level proficiency in Python, including experience with frameworks such as FastAPI, Django, Flask, or PySpark.
• Solid understanding of core AI concepts: knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
• Demonstrated hands-on experience with generative AI frameworks/orchestration tools like Google ADK, LanGraph, LangChain, AutoGen, or CrewAI.
• Extensive experience with machine learning frameworks (TensorFlow, PyTorch) and libraries (Scikit-Learn, NumPy, Pandas).
• Proven experience in creating, deploying, and integrating MCPs into agentic AI systems.
• Deep familiarity with large language models (LLMs) (e.g., ChatGPT, Claude, Gemini, Llama) and their application in agentic systems.
• Strong experience in designing and implementing robust APIs for AI services.
• Proficient in software development best practices: Git, CI/CD, com…