Job Specifications
About the Role
We are seeking a seasoned AI Technical Architect to lead the design and implementation of enterprise-scale AI solutions. This role will bridge Generative AI, Agentic AI, and traditional machine learning with strong enterprise architecture practices, cloud-native deployment, and robust data analytics foundations. The ideal candidate has the ability to design end-to-end AI ecosystems, ensure scalability and compliance, and translate complex business needs into innovative, practical solutions.
Key Responsibilities
Define and lead the AI solution architecture across Generative AI, Agentic AI, and traditional ML/AI domains.
Collaborate with business stakeholders, data scientists, and engineering teams to design enterprise-scale AI systems that deliver measurable business outcomes.
Architect end-to-end AI pipelines covering data ingestion, processing, model development, deployment, monitoring, and governance.
Design cloud-native AI platforms leveraging AWS, Azure, or GCP services, ensuring scalability, security, and compliance.
Lead the integration of Agentic AI frameworks into enterprise workflows, enabling orchestration of multi-step, autonomous processes.
Provide technical leadership in data analytics, big data platforms, and real-time processing to support AI-driven insights.
Establish and enforce best practices for model lifecycle management (MLOps, LLMOps, monitoring, explainability, traceability).
Stay ahead of the evolving AI ecosystem and provide strategic recommendations on new technologies, tools, and frameworks.
Mentor and guide engineering teams on advanced AI architecture, design patterns, and implementation strategies.
Required Qualifications
10+ years of industry experience in solution/technical architecture, including at least 5+ years in AI/ML systems.
Hands-on experience with Generative AI (LLMs, diffusion models, RAG pipelines) and Agentic AI (orchestration frameworks, multi-agent systems).
Strong foundation in traditional AI/ML (supervised/unsupervised learning, predictive modeling, NLP, computer vision).
Proven track record of designing enterprise-grade architectures for large-scale AI/analytics solutions.
Deep knowledge of cloud platforms (AWS, Azure, GCP) and their AI/ML services.
Expertise in data architecture & analytics (data lakes, data warehouses, big data ecosystems, BI platforms).
Understanding of compliance and governance requirements for AI in regulated industries (explainability, auditability, ethical AI).
Strong programming and architecture skills with Python, Java, or similar; exposure to AI frameworks (TensorFlow, PyTorch, LangChain, etc.).
Excellent communication and leadership skills; ability to translate between technical and business stakeholders.
Preferred Qualifications
Experience implementing Agentic AI systems at enterprise scale.
Familiarity with DevOps/MLOps/LLMOps pipelines and monitoring tools.
Exposure to industry-specific compliance frameworks (e.g., GxP in life sciences, HIPAA in healthcare, GDPR for data privacy).
Experience in data-driven product development and partnering with cross-functional business units.