AI Architect
ZEISS (company site, opens in a new tab)7+ yrsBengaluruOn-siteDirect career pageEst. 25–45 LPA
Posted 8h ago
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Job description
Structured overview of role & requirements
About This Role
- Own the technical product and engineering lifecycle of ZEISS’s Microsoft-based agentic AI solution for REF program and portfolio management, including architecture, productionization and internal support.
- Build secure data integrations and a shared project fact base, then deliver traceable AI capabilities for status reporting, management briefings, evidence-based Q&A, risk analysis and planning.
- Set and enforce technical standards for authorization, auditability, quality and releases; improve reliability and reduce manual reporting effort as the solution scales across REF projects.
Minimum Requirements
- Work Experience Required: Typically 7+ years in hands-on software, cloud or data engineering, including substantial experience designing production-grade AI, analytics or integration solutions.
- Graduate degree in Computer Science, Data Engineering, Software Engineering, Information Systems or a related discipline.
- Demonstrated experience taking AI, data or software pilots into secure, scalable production; practical experience with GenAI/agentic AI patterns such as RAG, orchestration, evaluation and human-in-the-loop controls.
- Strong practical Microsoft/Azure ecosystem, data engineering and production programming skills, plus experience with enterprise security, access control, auditability and responsible AI.
Ideal Candidate Profile
- A hands-on production engineer who can assess pilot architecture and code, convert prototypes into maintainable enterprise systems, and establish operational ownership and support.
- Has experience connecting structured and unstructured enterprise data and building grounded, traceable AI outputs with clear authorization, monitoring and data-quality controls.
- Regulated-industry or MedTech experience is preferred; success also depends on coordinating across IT, data/tool owners and global teams, while learning the REF domain.