GEN AI Lead Developer

Oversee the end-to-end development lifecycle of generative AI-based
solutions, ensuring timely and high-quality delivery.
-Write, review, and optimize code for AI models, APIs, user interfaces,
and backend services using best practices.
-Provide technical direction and mentorship to the development team,
fostering a culture of continuous improvement and innovation.
-Work closely with the Solution Architect to translate architectural
designs into functional software components.
-Implement and fine-tune pretrained models such as Granite, Mistral,
and Llama 3 within the watsonx framework.
-Leverage IBM’s watsonx platform to enhance generative AI
capabilities, ensuring optimal performance and scalability.
-Develop and deploy AI solutions on IBM Cloud, utilizing cloud-native
services for compute, storage, networking, and AI-specific offerings.
-Collaborate with data scientists, UX/UI designers, product managers,
and other stakeholders to integrate AI components seamlessly into th
overall solution.
-Communicate progress, challenges, and technical decisions effectively
to both technical and non-technical stakeholders.
-Participate in Agile/Scrum ceremonies, contributing to sprint
planning, daily stand-ups, and retrospectives to ensure project
alignment and continuous delivery.
-Ensure high standards of code quality through regular code reviews,
automated testing, and adherence to coding standards.
-Develop and implement comprehensive testing strategies, including
unit, integration, and system testing to ensure robust and reliable
solutions.
-Optimize AI models and applications for performance, scalability, and
cost-efficiency on IBM Cloud.
-Keep abreast of the latest advancements in generative AI, IBM Cloud
services, and relevant technologies to continuously enhance the
solutions.
Identify and implement improvements in development processes,
tools, and methodologies to increase team efficiency and product
quality.
-Maintain comprehensive technical documentation, including code
documentation, API specifications, and deployment guides.
-Implement security best practices in the development lifecycle,
ensuring that solutions comply with IBM’s security policies and
industry standards.
-Ensure that data handling within AI solutions adheres to data privacy
regulations and best practices