Generative Ai

**Summary**:
Generative AI (GenAI) Solution Architect is responsible for designing, developing, and implementing cutting-edge generative AI solutions tailored to meet business needs. This role requires deep technical expertise in AI, particularly in generative models and the ability to translate complex business requirements into scalable, efficient AI systems. The GenAI Solution Architect will collaborate with cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders, to drive AI innovation and ensure successful deployment and integration of AI solutions.

**Your role in our mission**:
**Technical Expertise & Essential Job Functions**
- Develop and maintain the enterprise architecture framework, ensuring alignment with organizational goals and industry best practices.
- Design and implement scalable, high-performance, and secure architecture solutions leveraging J2EE, Spark, and Python.
- Drive the adoption of cloud technologies (AWS and Azure) and integrate them effectively within the enterprise ecosystem.
- Evaluate and recommend emerging technologies, including AI/ML and GenAI, to enhance business processes and drive competitive advantage.
- Lead cross-functional teams to deliver complex projects, providing architectural guidance and ensuring adherence to best practices.
- Collaborate with stakeholders to define architectural requirements and ensure alignment with business objectives.
- Mentor and support other architects and technical team members, fostering a culture of innovation and excellence.
- Oversee the integration of new technologies and tools into the existing enterprise architecture, ensuring seamless interoperability.
- Leverage knowledge of the Healthcare and Life Sciences domains to provide specialized architectural solutions that address industry-specific challenges and regulatory requirements.
- Design solutions that support data interoperability, patient privacy, compliance, and advanced analytics in the healthcare and life sciences sectors.
- Establish and enforce architectural standards, guidelines, and policies to ensure consistency and compliance across projects and systems.
- Monitor and address architectural risks, ensuring that solutions are robust, secure, and scalable.
- Ensure models are deployed in a secure, scalable, and cost-effective manner, leveraging cloud platforms (e.g., AWS, Azure, Google Cloud).
- Conduct research and feasibility studies to explore new technologies, tools, and frameworks that can enhance AI capabilities.
- Ensure AI solutions comply with ethical standards, data privacy regulations, and organizational policies.
- Maintain comprehensive documentation for AI models, algorithms, and solutions, including design decisions, assumptions, and technical specifications.
- Conduct training sessions, workshops, and knowledge-sharing sessions to disseminate AI knowledge and best practices across the organization.
- Create and maintain reusable assets, frameworks, and tools to accelerate future AI development projects.
- Identify opportunities for architectural improvements and drive initiatives to enhance performance, efficiency, and cost-effectiveness.
- Lead the development and optimization of generative AI models, including model selection, training, fine-tuning, and validation.
- Work closely with product managers, business analysts, and stakeholders to gather and understand business requirements.
- Translate business needs into technical specifications and AI-driven solutions.
- Present AI solutions, architecture designs, and technical concepts to non-technical stakeholders to facilitate understanding and decision-making.

**What we're looking for**:

- Bachelor's degree in computer science, information systems, or related field preferred
- Proven experience of 20+ years of Technical experience in delivering business value and measure relevancy across product, process, functions and technology.
- Experience with MLOps, AI model deployment, and production environments.
- Certifications in cloud platforms (AWS Certified Machine Learning, Azure AI Engineer, etc.).
- Experience working with technical products, vendors, and families of technologies.
- Experience working with product configurations.
- Experience working with relevant software packages or classes of packages, and products within area of technical expertise.
- Good in technical design skills
- Good communication skills to communicate with customers, support personnel, and management.
- Good analytical and problem-solving skills
- Good organization skills to balance and prioritize work.
- Ability to handle multiple tasks simultaneously and switch between tasks quickly.
- Ability to work independently and as part of a team.

**Work Environment**
- Office / Hybrid / Remote environment
- May require evening work for onshore-offshore sync-up