Position : Generative AI Architect

Location : Pune - Godrej Castlemaine (Bund Garden road) next to Ruby Hall Clinic

Job Summary :

We are looking for an experienced GenAI Architect with deep expertise in Large Language Models (LLMs), Generative AI platforms, and cloud-native AI architectures, particularly on Microsoft Azure. The role involves designing and owning end-to-end GenAI platforms, including RAG architectures, vector databases, multi-tenant systems, and secure enterprise deployments.

The ideal candidate will combine strong hands-on technical depth, architecture ownership, and technical leadership, with good-to-have exposure to the medical/healthcare domain.

Core Technical Skills :

Generative AI & LLM Expertise :

- Deep understanding of Generative AI, GPT models, Transformer architectures, and fine-tuning techniques.

- Hands-on experience with Azure OpenAI, OpenAI APIs, or similar GenAI platforms.

- Strong expertise in prompt engineering, function calling, and LLM orchestration frameworks.

RAG (Retrieval-Augmented Generation) Architecture :

- Strong knowledge of RAG design patterns and enterprise GenAI architectures.

- Experience working with vector databases such as Azure AI Search, Milvus, Pinecone, Weaviate, or equivalent.

- Ability to design scalable, low-latency retrieval pipelines.

Embedding & Indexing :

- Experience with embedding models and indexing strategies.

- Hands-on knowledge of FAISS, HNSW, IVF, or similar indexing algorithms.

- Expertise in document chunking, metadata enrichment, and indexing optimization.

Cloud & Platform Architecture (Azure Preferred) :

- Strong expertise in Microsoft Azure, including :

1. Azure OpenAI

2. Azure AI Search

3. Azure Cognitive Services

4. AKS (Azure Kubernetes Service)

5. Azure Key Vault

- Experience with VNET integration, private endpoints, and secure cloud networking.

- Strong understanding of cloud security, IAM, and secrets management.

Multi-Tenancy & Security :

- Design and implementation of multi-tenant GenAI platforms.

- Experience with tenant isolation strategies: full isolation, hybrid, and shared models.

- Strong knowledge of authentication and authorization using Azure AD, RBAC.

- Ensure data privacy, security, and compliance (GDPR, HIPAA exposure preferred).

CI/CD, DevOps & MLOps :

- Experience building CI/CD pipelines for GenAI services using Azure DevOps, GitHub Actions, or similar tools.

- Automate model deployments, embedding generation, and index refresh workflows.

- Experience with Docker, Kubernetes, and cloud-native DevOps practices.

Monitoring & Observability :

- Implement logging, monitoring, and alerting using Azure Monitor, Application Insights, and OpenTelemetry.

- Define and track KPIs for GenAI systems including latency, accuracy, cost, and security metrics.

Roles & Responsibilities :

Architecture Design :

- Design and own end-to-end GenAI platform architecture, including :

1. LLM integration

2. RAG pipelines

3. Vector databases

4. Multi-tenant deployment models

- Define common backend components such as embedding services, orchestration layers, and retrieval pipelines.

- Create scalable front-end frameworks for chatbot and GenAI interfaces.

Technology Evaluation & Strategy :

- Evaluate and recommend LLMs (Azure OpenAI, OpenAI, Hugging Face, etc.).

- Assess and select vector databases and retrieval technologies.

- Evaluate solutions for security, compliance, scalability, and cost optimization.

- Influence enterprise GenAI strategy and roadmap.

Collaboration & Leadership :

- Collaborate closely with data engineers, cloud architects, product owners, and domain experts.

- Provide technical mentorship and best practices to AI/ML and engineering teams.

- Act as a GenAI thought leader within the organization.

Good to Have :

- Experience in medical devices, healthcare, life sciences, or clinical systems.

- Exposure to regulated environments and compliance standards.

- Experience with product engineering and enterprise SaaS platforms.

Education :

- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, Electronics, Biomedical Engineering, or related fields.