Information and Organisation Professionals

Wipro; Sydney; On-site; AUD 180,000 - 260,000; Full time

Job summary

Wipro is seeking a Senior AI Solutions Architect in Sydney to design end-to-end AI architectures aligned with business objectives. You will translate complex requirements into scalable, secure architectures and lead the adoption of AI/ML platforms across cloud ecosystems.

The role requires 8+ years IT experience, strong knowledge of MLOps, data architectures, and governance, with a focus on responsible AI and stakeholder engagement.

Qualifications

• 8+ years of IT experience with 4–5 years in solution architecture, AI/ML, data platforms or analytics.
• Hands-on knowledge of AI/ML concepts including ML, DL, NLP and model lifecycle management.
• Experience architecting solutions on cloud platforms (Azure, AWS or GCP) with data/storage/compute patterns.
• Strong data architecture understanding: data lakes, data warehouses, streaming, ETL/ELT.

Responsibilities

• Design end-to-end AI architectures aligned to business objectives.
• Identify AI use cases with stakeholders and define solution roadmaps and reference architectures.
• Lead selection and integration of AI/ML platforms, data platforms and cloud tooling.
• Define data, model, and integration architectures across deployment lifecycle.
• Provide governance and technical leadership for security, privacy and responsible AI.
• Guide teams on MLOps, deployment patterns, and production monitoring.
• Conduct solution reviews, PoCs, and technical assessments for feasibility and cost.

Skills

AI/ML concepts

Machine learning

Deep learning

Generative AI

NLP

Model lifecycle management

MLOps

CI/CD

Security & privacy

Responsible AI

Solution architecture

Cloud platforms

Education

Bachelor degree (CS/Engineering/Data Science)

Tools

Azure

AWS

GCP

Job description

Design and architect end‑to‑end AI solutions aligned to business objectives, translating complex requirements into scalable, secure, and high‑performing architectures.

• Collaborate with business stakeholders, product owners, and engineering teams to identify AI use cases and define solution roadmaps and reference architectures.
• Lead the selection, integration, and optimization of AI/ML platforms, data platforms, cloud services, and tooling across the solution stack.
• Define data, model, and integration architectures, ensuring robustness across data ingestion, model development, deployment, monitoring, and lifecycle management.
• Provide architectural governance and technical leadership, ensuring solutions adhere to enterprise standards, security, privacy, and responsible AI principles.
• Guide development teams on best practices for AI/ML engineering, MLOps, and scalable deployment patterns in cloud and hybrid environments.
• Conduct solution reviews, proofs of concept, and technical assessments to validate feasibility, performance, and cost‑effectiveness of AI solutions.
• Act as a trusted technical advisor to clients and internal teams, supporting pre‑sales activities, solution proposals, and executive‑level technical discussions.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related discipline; a Master’s degree or relevant AI/Cloud certifications is preferred.
• 8+ years of overall IT experience, with at least 4–5 years in solution architecture, AI/ML, data platforms, or advanced analytics roles.
• Strong hands‑on knowledge of AI/ML concepts, including machine learning, deep learning, generative AI, NLP, and model lifecycle management.
• Proven experience architecting solutions on cloud platforms (Azure, AWS, or GCP), including AI services, data storage, compute, and integration patterns.
• Solid understanding of data architectures, including data lakes, data warehouses, streaming, and ETL/ELT pipelines.
• Experience with MLOps practices, model deployment, monitoring, CI/CD, and scalable production environments.
• Strong stakeholder management and communication skills, with the ability to explain complex AI solutions to technical and non‑technical audiences.
• Experience in defining enterprise‑grade architectures with a focus on security, privacy, compliance, and responsible/ethical AI practices.