Job Description

Key responsibilities

Lead the AI Practice, defining the vision, roadmap, and strategy for AI adoption across the organization.
Oversee solution architecture and delivery of AI initiatives leveraging LLMs, RAG frameworks, and enterprise data platforms.
Provide thought leadership on emerging AI technologies, frameworks, and best practices.
Establish frameworks, governance, and reusable components for scalable AI implementation.
Establish AI architecture principles, standards, and governance frameworks across the organization.
Drive development of reusable solution accelerators, reference architectures, and best practices
Build and mentor a strong AI and data science team, fostering innovation and collaboration.
Represent the AI Practice in client discussions, steering PoCs and solution proposals for business impact.

Architecture & Solution:

Oversee end-to-end design and delivery of AI solutions including agentic workflows, RAG systems, LLM-powered applications, and ML models integrated into enterprise platforms.
Guide architecture reviews, technical design validations, and PoC direction for AI initiatives.
Ensure alignment of AI solution design with cloud-native, microservices-based, and containerized deployment models.
Partner with enterprise data and ML teams to align AI strategy with organizational goals and data maturity.

Innovation & Technology Leadership

Guide teams on leveraging tools such as LangChain, LlamaIndex, vector databases, and orchestration frameworks.
Promote adoption of modern MLOps practices including lifecycle management, deployment, monitoring, and evaluation of AI models.
Rapid innovation while ensuring enterprise-grade scalability and reliability.

Stakeholder & Business Engagement

Collaborate with CXOs, business heads, and technology leaders to identify, prioritize, and execute AI opportunities.
Represent the AI Practice in client engagements, supporting solution proposals, PoCs, and RFP responses.
Translate complex AI concepts into clear strategic insights for senior stakeholders.

CoE & Organizational Contribution

Contribute to the AI Center of Excellence by driving standardization, documentation, and knowledge sharing.
Establish evaluation frameworks for model performance, risk, and responsible AI usage.
Influence enterprise architecture decisions and cross-functional technology roadmaps.

Qualifications

Requirements

Overall 20+ years of experience in IT. Proven experience in leading AI strategy, architecture, and delivery at an enterprise or practice level.
Deep knowledge of AI solution design principles, prompt optimization, and enterprise AI deployment models.
Exposure to at least one major cloud AI platform (AWS / Azure / GCP).
Strong familiarity with MLOps concepts and enterprise data/AI platforms.
Strong stakeholder management, communication, and cross-functional leadership skills.
Demonstrated ability to translate emerging AI capabilities into actionable business outcomes.
Strategic mindset with experience in building and scaling AI teams and practices.

Technical & Domain Knowledge

Strong understanding of LLM orchestration tools and frameworks.
Familiarity with vector databases and LLM APIs (OpenAI, Azure OpenAI, HuggingFace, Cohere).
Knowledge of AI solution design, prompt optimization, and deployment models.
Awareness of ML/DL frameworks and data engineering ecosystems.
Understanding of cloud-native and containerized environments for AI workloads.

Leadership & Behavioral Skills

Exceptional stakeholder management and executive communication ability.
Strategic mindset with the ability to convert emerging AI capabilities into business impact.

Track record of guiding cross-functional teams and influencing decisions