AI/ML Architect

Qualifications:

• Software Engineering Architect / Lead with 10+ years of experience in designing and leading AI/ML and RPA solutions.
• Experienced in driving technical architecture, solution design, automation, and end-to-end software engineering initiatives.
• Strong leadership in guiding teams, defining scalable solutions, and collaborating with stakeholders to deliver business-focused technology solutions.

Strategy and use-case portfolio

• Build and own the AI, machine learning and RPA use-case pipeline: source candidate use cases from the business, size value and feasibility, and sequence them honestly.
• Make and defend build-versus-buy decisions, including where embedded vendor AI — SAP Joule, Manhattan's agentic capabilities, Microsoft Copilot, Shopify's native tooling — is the better answer than a custom build.
• Say no to use cases that do not survive scrutiny, and document why.

Architecture and delivery

• Own the reference architecture for machine learning and generative AI at Organization: data access patterns against Snowflake, model hosting, retrieval-augmented generation, evaluation, monitoring and MLOps.
• Own the RPA architecture and platform selection for finance and supply chain back-office automation, with a clear position on where process redesign beats automation of an existing bad process.
• Deliver the first production use cases personally alongside a small team — this is a hands-on role, not a strategy function.

Governance, risk and data protection

• Establish Organization's AI governance framework: use-case approval, model risk assessment, human-in-the-loop requirements, bias and fairness testing, and model lifecycle management.
• Define what corporate, customer and employee data may and may not be used in AI systems, working with Information Security and Legal, under GDPR and CCPA obligations.
• Ensure no personally identifiable or payment data enters model training, prompting or third-party AI services without explicit approved control.
• Own the position on third-party AI vendor assessment and data residency.

Leadership and enablement

• Hire and lead a small team of AI, machine learning and RPA engineers.
• Act as Organization's internal translator on AI — set realistic expectations with business stakeholders, and counter both overclaiming and reflexive scepticism with evidence.
• Partner with the Snowflake Lead to ensure the data platform is fit for purpose for AI workloads.

Preferred:

• Retail, consumer goods or apparel use cases: demand forecasting, assortment planning, inventory optimisation, pricing or customer service automation.
• Experience with AI capabilities embedded in SAP, Microsoft, Shopify or Manhattan platforms.
• Experience building an AI function from a standing start.
• Snowflake or comparable cloud data platform experience as the foundation for ML workloads.

Note: Shortlisted candidates must be available to attend a face-to-face interview in Hyderabad.