Senior AI​/ML Engineer - Engineering Excellence; Full Stack Developer Vice President

Position: Senior AI/ML Engineer - Engineering Excellence (Full Stack Developer) Vice President
For additional information, please review .We are seeking a highly skilled and experienced
** Senior AI/ML & Agentic AI Engineer
** with a robust background in
** Python, Java, database technologies, cloud platforms, and CI/CD Dev Ops practices
** to join our
** Engineering Excellence and Transformation
** organization. In this critical role, you will be at the forefront of designing, developing, and integrating cutting-edge AI/ML and Agentic AI solutions, including advanced AI assistant tools, to revolutionize engineering processes and drive significant operational improvements across our enterprise. You will leverage your comprehensive technical expertise to build scalable, resilient, and high-performance AI systems from conception to deployment, fostering a culture of innovation and continuous delivery.
* Lead the design, development, and implementation of sophisticated AI/ML, Generative AI, and Agentic AI solutions, including AI assistant tools, in close collaboration with AI architects, product owners, and cross-functional engineering teams within the Engineering Excellence framework.
* Architect and develop end-to-end AI systems, leveraging both Python for machine learning workflows and Java for scalable enterprise-grade backend services, ensuring seamless integration with existing and new applications.
* Design and implement intelligent agentic systems that exhibit autonomous decision-making capabilities, enabling advanced automation and self-optimizing processes.
* Develop, fine-tune, and optimize Large Language Models (LLMs) using both parameter-efficient techniques and full fine-tuning, focusing on their integration into robust, production-ready systems supported by both Python and Java components.
* Drive the implementation and experimentation with advanced generative AI methods such as prompt engineering and Retrieval-Augmented Generation (RAG), ensuring their effective deployment and performance in enterprise environments.
* Own the deployment pipeline for AI models and associated services, leveraging CI/CD methodologies, containerization (Docker), and orchestration (Kubernetes) on leading cloud platforms (AWS, Azure, GCP) to ensure secure, scalable, and automated releases.
* Apply deep knowledge of database technologies (SQL and No

SQL) to design efficient data storage, retrieval, and management strategies for AI applications, ensuring data integrity and performance.
* Contribute to the establishment and enforcement of engineering best practices, architectural patterns, and tooling standards for full-stack AI development, advocating for maintainability, observability, and cost-efficiency.
* Stay abreast of the latest advancements in AI/ML, Agentic AI, cloud technologies, and Dev Ops trends, proactively sharing knowledge and driving adoption of innovative solutions.
* Ensure strict adherence to ethical AI guidelines, data privacy regulations, and compliance standards throughout the entire AI solution lifecycle.
* Act as a mentor for junior engineers, providing expert guidance on Python, Java, cloud technologies, and CI/CD best practices, fostering a culture of technical excellence and continuous improvement.
* ** Python:
** Expert proficiency in Python for AI/ML development, including data manipulation (Pandas), scientific computing (Num Py), and machine learning frameworks.
* ** Java:
** Strong proficiency in Java (e.g., Spring Boot, Microservices, Enterprise Integration Patterns, RESTful APIs) for building scalable, high-performance, and resilient enterprise applications.
* Extensive experience with Generative AI, Agentic AI principles, and the development of AI assistant tools.
* Hands-on experience with LLMs and fine-tuning methods (e.g., LoRA, QLoRA, Adapter/Prefix Tuning, instruction tuning).
* Practical knowledge of model optimization techniques (e.g., compression, quantization) and familiarity with tools such as Deep Speed, vLLM, GPTQ, or similar.
* Proficient in prompt engineering, prompt design tools/frameworks, and building robust RAG systems (hybrid search, multi-vector retrieval).
* Proficient with machine learning frameworks (PyTorch, Tensor Flow, Keras) and distributed training.
*…