Solutions Architect

ZEISS VisioGen; Bengaluru; Hybrid; INR 3,000,000 - 7,000,000; Full time

Job summary

ZEISS VisioGen, Bangalore preferred (Hybrid); India locations considered, seeks a Solution Architect to own the VisioGen platform architecture and drive AI-native, secure, scalable solutions for ophthalmology clinics worldwide.

You will design systems, contribute production code, set engineering standards, and mentor a growing team, bridging business, product, IT, and clinic partners while delivering reliable, compliant software at scale.

Qualifications

• 12–20 years of software engineering experience.
• 5+ years designing and scaling distributed SaaS products in production.
• Hands-on Azure & .NET Core experience.
• Hands-on GenAI delivery experience in production.
• Strong experience with microservices, containers, event-driven services, Kubernetes (AKS preferred), CI/CD, and release management.
• Proven experience mentoring engineers and shaping teams.

Responsibilities

• Own the Platform Architecture across VisioGen, including multi-tenant, secure, scalable design.
• Build cloud-native .NET Core microservices on Azure (AKS, App Services/Functions, Service Bus, Cosmos DB).
• Drive AI-native SDLC and implement spec → code → test → release workflows.
• Own React/TypeScript engagement layer and plug-and-play integrations.
• Establish CI/CD, release management, feature flags, and safe rollouts.
• Ensure HIPAA/GDPR compliance and PHI protection principles in design.

Skills

Distributed systems

.NET Core / C#

Azure

GenAI delivery

Microservices & Kubernetes

CI/CD & release mgmt

AI-assisted development tools

Tools

Azure DevOps

GitHub Actions

Job description

Location: Bangalore preferred (Hybrid); other India locations considered

Experience: 12–20 years

Reports to: Head of Product & Engineering, ZEISS VisioGen

About ZEISS VisioGen

ZEISS VisioGen is building the future of AI-powered healthcare by developing human-verified clinical communication solutions for ophthalmology practices.

We combine cutting-edge Generative AI with clinical expertise to build scalable, production-ready applications that enhance patient engagement and improve healthcare delivery.

The Role

As a Solution Architect, you will own the technical architecture of the VisioGen platform and build it alongside the team.

You will design the system, contribute production code, set engineering standards, and help grow the team that scales the platform across clinics worldwide.

The role acts as a bridge between business, product, engineering, IT, customer success, and external clinic partners—turning business needs into practical, secure, and scalable technology solutions.

This is a hands-on architecture role. A significant part of your time will go into design, coding, code reviews, and proofs of concept, alongside technical leadership.

What You Will Do

1. Own the Platform Architecture

• Design and evolve the end-to-end architecture of VisioGen, including patient chat, AI response generation, human clinical review, clinic escalation, analytics, and integrations.
• Build cloud-native .NET Core microservices on Azure, including AKS, App Services/Functions, Service Bus, Azure SQL/Cosmos DB, Entra ID, Key Vault, and API Management.
• Design for multi-tenancy, security, scalability, reliability, performance, and cost as the platform grows from tens to thousands of clinics.
• Convert business and customer requirements into clear technical solution designs and efficient event-driven frameworks.
• Make and document architecture decisions (ADRs) and lead design reviews.
• Drive integrations with practice-management systems, EHRs/EMRs, and patient channels such as WhatsApp, web chat, LINE, Viber, and Facebook Messenger.
• Ensure release reliability against measurable SLAs/SLOs.

2. Optimize & Scale the AI Engine

• Work with AI leads to optimize production GenAI pipelines, including RAG, chunking, embeddings, hybrid search, reranking, agentic workflows, tool calling, orchestration, state management, prompt management, and model routing.
• Strengthen AI quality through robust evaluations while maintaining accuracy, explainability, and low latency.
• Design human-in-the-loop verification, including review queues, confidence thresholds, escalation, and audit trails.
• Optimize token usage and AI operating costs.

3. Drive an AI-Native SDLC

• Make AI-assisted engineering the default using tools such as GitHub Copilot, Claude Code, and Cursor.
• Drive spec-driven development and AI-assisted testing and code review.
• Define and continuously improve the spec → code → test → release → operations workflow.
• Establish coding standards, testing strategies, and engineering quality standards.

4. Full-Stack Ownership & Integrations

• Guide and harden VisioGen’s React / TypeScript engagement layer, including the patient chat widget, clinic dashboards, and reviewer consoles.
• Design a plug-and-play integration architecture for APIs, webhooks, FHIR contracts, and events across clinic websites, EHRs, CRMs, scheduling systems, and marketing tools.
• Ensure compliance with HIPAA/GDPR and PHI-protection requirements.

5. Release Management & ZEISS Software Development Process

• Establish an efficient commercial release process aligned with ZEISS software delivery requirements.
• Own CI/CD and environment strategy using Azure DevOps or GitHub Actions, including versioning, feature flags, safe rollouts, and rollback mechanisms.
• Define release dependencies, branching, and merge strategies.
• Enable continuous delivery with measurable metrics, including DORA.
• Collaborate with ZEISS Central IT on approved and compliant architecture approaches.

6. Security & Compliance by Design

• Build HIPAA-aligned data flows with GDPR and global readiness.
• Cover PHI handling, encryption, access control, data retention, and audit logging.
• Represent the architecture in ZEISS IT, InfoSec, and compliance reviews.
• Produce required data-flow and threat-model documentation.

7. Build & Mentor the Team

• Help shape the engineering team’s structure, roles, and hiring.
• Mentor engineers on architecture, distributed systems, and AI engineering.
• Develop technical leaders within the team.
• Partner with product teams to assess feasibility, estimate work, and shape the roadmap.

8. Cross-Functional Collaboration

• Collaborate with sales, customer success, doctors, clinical operations, engineering, product, IT, and external clinic stakeholders.
• Act as the technical owner during clinic implementations and post-go-live stabilization.
• Explain technical capabilities and trade-offs clearly to clinicians and business leaders.

What You Bring

Must-Have

• 12–20 years of software engineering experience, including 5+ years designing and scaling distributed systems or SaaS products in production.
• Deep, recent, hands-on experience with .NET Core / C#.
• Strong hands-on experience with Microsoft Azure.
• Hands-on GenAI delivery experience—you have personally built and shipped RAG and/or agentic systems to production.
• Strong experience with microservices, containers, event-driven services, Kubernetes (AKS preferred), CI/CD, and release management.
• Practical experience using AI-assisted development tools in daily engineering work.
• Proven experience structuring teams and mentoring engineers.
• Strong problem-solving skills with examples of complex technical challenges you have solved.

Preferred

• Product-company background, including SaaS, startups, or product-engineering teams.
• Healthcare technology experience involving HIPAA, GDPR, PHI, HL7/FHIR, EHR/EMR integrations, patient engagement, or clinical workflows.
• Experience with WhatsApp Business API, LINE, Viber, Messenger, or chatbot products.
• Integration experience with CRMs, scheduling systems, or marketing platforms.
• Experience with LLM evaluation frameworks, vector databases, and AI observability tools.
• Experience working in regulated or gated software-release environments.
• Experience working with US customers or global teams.

How We Will Assess

• Architecture Deep-Dive: Walk us through a system you designed and scaled, including key trade-offs and what broke.
• Case Study: Practical system-design case study with a hands-on technical deep dive.
• AI Depth: How you would build a human-verified RAG pipeline with evaluation and guardrails.
• Leadership: How you have structured teams, mentored engineers, and raised engineering standards.

Interested?

If you’re a hands-on technology leader who enjoys architecting, coding, scaling AI systems, and building strong engineering teams, we’d love to hear from you.

Join ZEISS VisioGen and help us build scalable, AI-powered healthcare technology for ophthalmology practices worldwide.