
Chief Artificial Intelligence Architect
1 day ago
Job Title / Role:
We are seeking a highly skilled Gen AI Sr Architect with strong AI/ML expertise and consulting experience to lead client engagements, identify AI/GenAI opportunities across business operations, customer experience, and new revenue streams.
Key Responsibilities:
- Consulting & Advisory: Engage with senior stakeholders across client organizations to understand business pain points and strategic goals. Identify opportunities where GenAI/AI/ML can create tangible business impact (operational efficiency, customer experience, new revenue models). Conduct GenAI ideation workshops, PoC scoping, and value realization assessments.
- Solution Architecture: Design scalable GenAI and traditional AI/ML solutions based on client use cases. Select appropriate LLMs, architectures (RAG, fine-tuning, agents), and platforms (Azure OpenAI, AWS Bedrock, etc.). Define security, data governance, and compliance aspects for GenAI applications.
- Stakeholder Engagement: Present solution blueprints and roadmaps to business and technology leaders. Act as a bridge between client stakeholders, business teams, and internal delivery squads. Coordinate with client's technical architects to align with existing systems and frameworks.
- Delivery Oversight: Guide and mentor delivery teams during design, development, and deployment. Support pre-sales efforts by creating proposals, estimates, and case studies. Track project progress, remove roadblocks, and ensure quality delivery.
- Innovation & Thought Leadership: Stay updated with the latest GenAI models, tools, and industry use cases. Build reusable accelerators, frameworks, and reference architectures. Contribute to internal knowledge sharing and competency building.
Qualifications:
- Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. 12+ years of experience in AI/ML including deep learning, NLP, predictive analytics.
- 2+ years of experience in building and deploying GenAI-based solutions (e.g., using GPT, Claude, Gemini, LLaMA, etc.).
- Strong understanding of GenAI concepts: LLMs, RAG, agents, embeddings, prompt engineering.
- Hands-on experience with platforms like OpenAI, Azure OpenAI, AWS Bedrock, LangChain, LlamaIndex, etc., ML.
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