AI Architect

Role:AI Architect

Exp: 10 to 15 yrs

Location: Chennai(Hybrid)

In non-cloud Large Language Model (LLM) deployments, the AI Architect serves as a strategic leader, driving the alignment of AI solutions with business objectives while addressing critical challenges like scalability, governance, and security. Their role ensures sustainable and impactful AI adoption across the organization, balancing technical innovation with business strategy.

Key Responsibilities

1. Strategic Planning and Road mapping

• Identify and prioritize AI use cases that align with organizational goals and deliver business value.
• Develop a phased roadmap for AI implementation, focusing on scalability and long-term sustainability.
• Conduct detailed cost-benefit analyses to ensure the return on investment (ROI) for deploying non-cloud LLMs.

2.Model and Architecture Design

• Select and fine-tune LLMs tailored to meet enterprise-specific requirements.
• Design robust inference pipelines to ensure high performance and seamless integration with existing systems.

3.Governance and Compliance

• Establish ethical AI frameworks to address issues like bias mitigation and safe deployment practices.
• Ensure compliance with global regulations such as GDPR and CCPA, adapting practices to meet industry standards.
• Foster transparency and fairness in AI operations, creating trust among stakeholders.

4.Collaboration and Team Alignment

• Act as a bridge between business, engineering, and data science teams to ensure seamless communication and project execution.
• Organize training sessions and workshops to upskill team members and promote AI literacy.
• Create feedback mechanisms to incorporate iterative improvements and refine AI solutions.

5.Lifecycle Management

• Automate pipelines for LLM training, deployment, and regular updates to minimize manual effort.
• Monitor key performance indicators (KPIs) to evaluate model performance and optimize processes continually.
• Oversee infrastructure management, ensuring the specific needs of non-cloud setups are met effectively.

6.Security and Risk Management

• Proactively address data security challenges and mitigate risks associated with compliance breaches.
• Develop detailed audit trails and protocols for explainability to ensure accountability and trustworthiness in AI solutions.
• Implement robust security measures tailored for on-premise LLM deployments.

Additional Notes:

This role demands a blend of strategic foresight, technical expertise, and leadership capabilities. The AI Architect will be required to travel frequently (30-40%) to client locations, including Riyadh, to oversee implementation, stakeholder alignment, and on-site support.