Data & Artificial Intelligence Architect

Description:

Position Specification:

Organisation is seeking a Data & AI Architect with deep expertise in designing and implementing solutions using Generative AI (GenAI), Large Language Models (LLMs), and Agentic AI frameworks. In this role, you will be responsible for architecting and developing enterprise-grade data and AI solutions that leverage these advanced technologies to drive innovation across company's business lines and product ecosystem.

You will collaborate closely with senior executives and cross-functional teams on high-impact, high-visibility initiatives. Your solutions will be market-tested and deployed to deliver measurable value in areas such as risk management, operational efficiency, and financial performance. This is a strategic, hands-on role that blends technical leadership with architectural vision to shape company's AI-driven future.

You Will:

Key Responsibilities:

- Architect Scalable Data & AI Solutions: Design and architect end-to-end data and AI systems, including data pipelines, model workflows, and AI services, ensuring scalability, reliability, and performance across enterprise use cases.

- GenAI Enablement: Help Integrate Generative AI capabilities such as entity extraction, summarization, and retrieval-augmented generation (RAG) into enterprise data platforms to enrich and contextualize data assets.

- Agentic AI Frameworks: Architect autonomous AI agent systems using frameworks like LangGraph, CrewAI, or similar, enabling multi-agent collaboration and orchestration for complex business tasks.

- AI/ML Strategy & Governance: Define and implement AI/ML architecture standards, model lifecycle governance, and responsible AI practices including bias testing, explainability, and ethical deployment.

- Cross-Functional Collaboration: Partner with Data Engineers, MLOps, and Platform teams to ensure seamless integration of AI models into production environments, including containerization, CI/CD pipelines, and monitoring.

- Tooling & Platform Standardization: Drive standardization of AI development tools, libraries, and infrastructure across teams to improve productivity, maintainability, and compliance.

- Advanced Analytics Enablement: Enable teams to build high-performing models by providing architectural guidance on model selection, and performance optimization.

- Data Architecture Alignment: Work closely with data architects to align AI solutions with enterprise data strategy, including data lakehouse design, metadata management, and data quality frameworks.

- Innovation & Thought Leadership: Stay ahead of emerging trends in AI, GenAI, and data architecture; evaluate new technologies and frameworks for adoption; and evangelize best practices across the organization.

- Stakeholder Engagement: Collaborate with business leaders, product owners, and domain experts to translate strategic objectives into AI-enabled solutions and ensure alignment with business goals.

- Communication: Provide architectural insights and solution roadmaps through clear documentation, visual models, and presentations to technical and non-technical stakeholders.

You are:

You are a technologist with a passion for architecting scalable and intelligent data and AI systems. You thrive on applying cutting-edge techniquesincluding Generative AI and Large Language Models (LLMs)to solve complex business challenges. You are deeply analytical, intellectually curious, and enjoy designing solutions that move from concept to deployment, delivering real-world impact.

You collaborate seamlessly with cross-functional teamsdata engineers, software developers, business analysts, and domain expertsto translate strategic goals into robust AI-enabled platforms. While your core strength lies in technical leadership and solution design, you also bring experience in guiding data science teams and engaging with senior business stakeholders to align technology with enterprise objectives.

You have:

- PhD with 6+ years of experience, Master's degree with 10+ years of experience, or Bachelor's degree with 15+ years of experience in Computer Science, Engineering, Applied mathematics or related field

- 5+ years of hands-on experience in architecting Data & AI Solutions

- Deep understanding of cloud-native architectures, microservices, containerization (Docker/Kubernetes), and CI/CD for AI/ML workflows

- Hands-on experience in architecting GenAI applications, including LLM orchestration, prompt engineering, and retrieval-augmented generation (RAG)

- Experience in model lifecycle management, including experimentation, versioning, monitoring, and retraining strategies

- Strong working knowledge of engineering components essential for GenAI applications, including vector databases, caching layers, chunking, and embedding techniques

- Solid background in algorithms and a wide range of ML models, with understanding of their trade-offs in real-world scenarios

- Excellent analytical and problem-solving abilities with strong attention to detail

- Proven leadership in providing technical guidance and mentoring to data science teams

- Strong communication skills and ability to collaborate cross-functionally with Product, Engineering, and Business teams at both strategic and hands-on levels

- Experience in deploying models in production environments and ensuring reliability, scalability, and governance through MLOps integration