- Integration and Deployment : Ensuring seamless integration of GenAI solutions with existing systems and cloud infrastructure, and overseeing the deployment and monitoring of the system in production.

- Innovation and Research : Staying up-to-date with the latest advancements in GenAI, including new algorithms, techniques, and hardware, and evaluating their potential for future projects.

Minimum Qualifications :

- Bachelors or Masters in Computer Science, Engineering, Data Science, or related technical field.

- Sound experience as solution Architect for large-scale AI/GenAI projects.

- Strong understanding of the GenAI lifecycle including data preparation, model training, evaluation, deployment, and monitoring.

- Excellent knowledge on Azure and basic knowledge in AWS

- Experience managing projects using Agile/Scrum methodologies.

- Familiarity with tools and platforms used in GenAI projects.

- Strong communication, stakeholder management, and problem-solving skills.

- Hand on experience in python

Preferred Qualifications :

- Azure Certified Solutions Architect.

- Working knowledge of cloud platforms (Azure and AWS/GCP) and CI/CD for ML systems.

- Experience working in manufacturing, retail, healthcare, or other domains where GenAI is applied.

- Exposure to data security and governance frameworks.

- Prior experience in industries like energy, heavy industrial equipment, power generation will be considered a significant value add.

Responsibilities :

- Requirements Gathering : Translating ambiguous, high-level product goals into concrete, actionable feature-level requirements and system specifications, considering constraints like performance, security, and scalability.

- Strategic Planning : Defining the overall technical vision for GenAI solutions, aligning them with business objectives and strategy.

- Solution Design : Creating detailed technical designs and architectures for GenAI systems, including selecting appropriate algorithms, hardware, and software components.

- Architect GenAI solutions

- Architect CI/CD pipeline for GenAI

- Architect GenAI API endpoints

- Documentation :

1. Review GenAI code documentation.

2. Review GenAI design documents (FDD and TDD)

- Technical Leadership : Guiding development teams throughout the project lifecycle, providing technical expertise, resolving issues, and ensuring adherence to best practices.

- Stakeholder Management : Collaborating with various stakeholders (business, engineering, product) to communicate technical concepts, manage expectations, and ensure alignment on project goals and progress.

- Performance Optimization : Debugging, optimizing, and fine-tuning GenAI solution for optimal performance, considering factors like latency, throughput, and resource utilization.