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Location
In office (Bengaluru)
Seniority
Architect · 7+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. Zeiss scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Zeiss is a German optics and optoelectronics group founded in Jena in 1846 that is owned by a foundation rather than by shareholders, which frees it to invest on very long horizons. Its most strategically important business supplies the optical systems inside extreme ultraviolet lithography machines, without which leading-edge semiconductor manufacturing would not be possible, and it also makes surgical and diagnostic ophthalmic equipment, spectacle lenses, industrial measurement systems, microscopes and camera optics. Headquartered in Oberkochen with a large site in Jena, the group employs tens of thousands of people and spends an unusually high share of revenue on research.

ZEISS in India

ZEISS in India is headquartered in Bengaluru and present in the fields of Industrial Quality Solutions, Research Microscopy Solutions, Medical Technology, Vision Care and Sports & Cine Optics.

ZEISS India has 3 production facilities, R&D center, Global IT services and about 40 Sales & Service offices in almost all Tier I and Tier II cities in India. With 2200+ employees and continued investments over 25 years in India, ZEISS’ success story in India is continuing at a rapid pace.

Further information at ZEISS India.

Duties and responsibilities

  • Act as technical product owner and lead engineer for Microsoft-based agentic AI solutions supporting REF program and portfolio management.
  • Take over externally and internally developed pilot components, assess their architecture and code quality, industrialize them, and establish sustainable internal ownership, documentation and support.
  • Design, build and maintain secure data pipelines and connectors for relevant sources such as Microsoft Teams chats and meeting transcripts, SharePoint, Excel, Jira, Azure DevOps, Smartsheet, eDMS and Polarion.
  • Create and maintain a common project fact base that links projects, tasks, milestones, dependencies, resources, decisions, risks, documents and meeting evidence.
  • Develop and orchestrate agents for project status reporting, management briefings, evidence-based Q&A, risk and dependency analysis, resource and capability planning, and scenario support.
  • Implement grounded retrieval, source attribution, data-quality checks and explicit gap handling so that every material output is transparent and reviewable.
  • Use approved Microsoft and Azure capabilities, including Microsoft 365, Teams, Power Platform, Copilot technologies, Azure AI services and Entra ID, in alignment with ZEISS architecture and security standards.
  • Implement identity, project-scoped authorization, audit logging, monitoring, model and prompt lifecycle management, testing, release management and incident support.
  • Collaborate with ZEISS IT, ZEISS Digital Partners, the MED AI Hub, data owners and tool owners to secure access, clarify interfaces and reuse existing enterprise platforms and components.
  • Partner closely with the Global Program Intelligence & Transformation Lead and all R&D projects to translate management questions into reliable technical products and measurable use cases.
  • Build reusable engineering patterns, technical documentation, runbooks and knowledge-transfer materials; coach additional engineers as the capability scales.
  • Continuously evaluate solution quality, cost, performance, security and user feedback and improve the platform based on evidence.

Authorities

  • Recommend technical architecture, engineering standards and release decisions for the REF agentic AI and Portfolio Intelligence solution within approved ZEISS guardrails.
  • Approve technical changes and deployments within the delegated product scope and defined change-control process.
  • Reject integrations or agent releases that do not meet agreed security, data-quality, traceability or maintainability criteria.
  • Coordinate technical work packages with internal teams and approved external engineering partners.

Qualifications

  • Graduate degree in Computer Science, Data Engineering, Software Engineering, Information Systems or a related discipline.
  • •Typically 7+ years of hands-on experience in software, cloud or data engineering, including substantial experience designing production-grade AI, analytics or integration solutions.
  • Proven experience taking AI, data or software pilots from proof of concept into secure, scalable and sustainably operated production solutions.
  • Demonstrated experience with GenAI and agentic AI patterns, including retrieval-augmented generation, tool/function calling, orchestration, evaluation, observability and human-in-the-loop controls.
  • Strong practical experience with the Microsoft ecosystem, preferably Azure AI services, Microsoft 365 / Graph integration, Teams, Power Platform, Copilot technologies, Azure DevOps and Entra ID.
  • Strong data-engineering skills across APIs, ETL/ELT, SQL and document or semantic retrieval; experience integrating structured and unstructured enterprise data.
  • Strong hands-on programming skills for production AI and data integrations (for example, Python), combined with sound software-engineering practices, automated testing, CI/CD and infrastructure-as-code exposure.
  • Experience with secure enterprise architecture, access control, auditability, data protection and responsible AI. Experience in regulated industries or MedTech is strongly preferred.
  • Excellent communication skills and the ability to collaborate across India, Germany and global virtual teams.

Success measures

  • Stable internal operation and maintainability of the solution.
  • Reliable, traceable access to agreed data sources with appropriate authorization and monitoring.
  • Accuracy, usefulness and user trust of agent-generated project and portfolio outputs.
  • Reduction in manual reporting effort and cycle time for management preparation.
  • Reuse of common components and controlled scale-up to additional REF projects and use cases.

Other attributes

We are looking for a hands-on builder and pragmatic problem solver, not only an AI concept expert. The successful candidate combines deep technical curiosity with production discipline, understands that enterprise AI is primarily a data, integration and governance challenge, and can translate an externally accelerated pilot into a robust ZEISS-owned capability. Willingness to learn the MedTech and REF domain is essential.

Direct reports

None initially; the role is expected to lead technical contributors and partners through matrix collaboration. Team build-up may follow based on scaling decisions beyond REF.

Your ZEISS Recruiting Team:

Saptarshi Chowdhury
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