Job Description

Key Responsibilities

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AI Solution Architecture

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- Design end-to-end AI, ML, GenAI, and Agentic AI architectures aligned to business outcomes.
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- Define solution blueprints covering data ingestion, model lifecycle, orchestration, deployment, monitoring, and governance.
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- Create architecture patterns and reusable frameworks that accelerate AI delivery.
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- Evaluate and select appropriate AI technologies, platforms, and tooling.
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Technical Leadership

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- Provide architecture leadership across multiple initiatives and delivery teams.
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- Guide engineering teams on architectural best practices and AI adoption.
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- Support architectural reviews, design governance, and technology decisions.
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- Collaborate with Enterprise Architecture and platform teams to align with strategic roadmaps.
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Generative AI & Agentic AI

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- Design architectures using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, orchestration frameworks, and agent-based systems.
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- Define patterns for prompt management, evaluation, observability, and AI safety controls.
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- Support the adoption of secure and governed GenAI capabilities across the organisation. [AI Enterpr...ategy v5.1 | PowerPoint], [Build your...n’t sure w | Viva Engage]
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Governance, Risk & Security

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- Ensure AI solutions comply with Responsible AI, security, privacy, and risk requirements.
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- Contribute to model governance, architecture standards, and technical assurance processes.
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- Partner with Cyber Security, Risk, and Compliance teams to design secure AI capabilities.
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- Embed monitoring, auditability, explainability, and operational controls into AI solutions. [AI Enterpr...ategy v5.1 | PowerPoint]
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Stakeholder Engagement

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- Translate complex technical concepts into business-friendly language.
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- Influence senior technical and business stakeholders.
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- Facilitate architecture workshops and solution design sessions.
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- Build strong relationships across product, engineering, architecture, and business teams.
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Essential Skills & Experience

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- Robust experience designing enterprise-scale AI and Machine Learning solutions.
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- Experience with Generative AI, LLMs, Agentic AI frameworks, and RAG architectures.
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- Expertise in cloud-native architecture, preferably Google Cloud Platform (GCP).
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- Knowledge of MLOps, LLMOps, model deployment, monitoring, and lifecycle management.
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- Experience with distributed systems, APIs, microservices, and event-driven architectures.
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- Strong architecture modelling, design documentation, and governance experience.
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- Understanding of Responsible AI, AI security, and regulatory considerations.
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- Excellent stakeholder management and communication skills.
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Preferred Technical Skills

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- Google Cloud Platform (Vertex AI, BigQuery, GCS).
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- Python and AI/ML ecosystems.
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- LangGraph, LangChain, ADK, orchestration frameworks.
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- Vector databases and Retrieval-Augmented Generation (RAG).
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- Kubernetes, Docker, CI/CD, DevOps practices.
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- Data architecture and data engineering concepts.
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- Enterprise integration and API management.
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Leadership Expectations

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- Act as a recognised technical leader within the AI architecture community.
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- Mentor Solution Architects, Engineers, and Data Scientists.
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- Drive adoption of architecture standards and best practices.
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- Promote innovation while maintaining strong governance and risk management.
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- Influence strategic technology decisions through thought leadership.
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Success Measures

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- Delivery of scalable and secure AI solutions.
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- Adoption of reusable architecture patterns.
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- Improved time-to-market for AI products.
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- Compliance with architecture, risk, and governance standards.
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Positive business outcomes through AI-enabled capabilities

📌 Director of Artificial Intelligence (Hyderabad)
🏢 Xander Talent
📍 Hyderabad