Gen AI Architect

Job Description :

- 10+ years in ML/Engineering.

- At least 5 years in architecture roles.

- Proven experience delivering production-grade solutions on Azure.

- Hands-on ownership of end-to-end application lifecyclefrom design to deployment.

- Proven track record of communicating complex technical concepts to both developer teams and executive stakeholders.

Responsibilities :

- Lead architecture and development of enterprise web applications with integrated Generative AI.

- Serve as a primary technical partner to clients and developers, guiding them from early experimentation through production scale deployments.

- Roll up your sleeves on POCs, prototypes, and pilots, and help clients operationalize them into production-grade systems.

- Design and validate end-to-end AI and GenAI solutions architectures spanning the full stack, from foundation model integration to agentic workflows, orchestration, evaluation, and observability.

- Define scalable, secure architectural patterns and implementation standards.

- Work closely with product, AI/ML, DevOps, security, and network teams to align business and technical goals.

- Drive full-stack development best practices across backend, frontend, and infrastructure.

- Architect and integrate LLMs, embeddings, RAG pipelines, and vector databases into production systems.

- Ensure production readinesssecurity, networking, monitoring, performance, and compliance.

Mandatory Technical Skills :

Cloud Architecture (Azure) :

- Deep experience designing cloud-native, microservices and event-driven architectures. Expertise with Azure App Services, AKS, Functions, API Management, Event Grid, Service Bus, Storage, and Key Vault.

- Strong understanding of subscription design, resource hierarchy, and environment isolation.

Networking & Security :

- Hands-on experience with :

1. VNETs, subnets, private endpoints, service endpoints.

2. NSGs, ASGs, routing, firewalls, and VPN/ExpressRoute connectivity.

3. Whitelisting, IP restrictions, certificates, TLS, and enterprise-grade authentication flows.

- Experience implementing Zero Trust, RBAC, managed identities, and secure secret handling.

Performance & Scalability :

- Expertise in caching (Redis/CDN), async processing (RabbitMQ/Kafka), load balancing, auto-scaling, and performance tuning.

GenAI Integration :

- Hands-on experience with Azure OpenAI, RAG patterns, embeddings, prompt engineering, vector search (Azure AI Search, PostgreSQL extensions).

- Experience orchestrating LLM pipelines in real-world production environments.

Backend Engineering :

- Strong REST API design (versioning, throttling, API gateways).

- Expert in PostgreSQL/MongoDB, data modeling, query optimization.

- Experience with OAuth2, SSO, and secure coding aligned to GDPR/SOC2.

Frontend Engineering :

- Deep experience with React/Next.js, component libraries, and enterprise UI patterns.

DevOps & IaC :

- Strong proficiency with :

1. Azure DevOps or GitHub Actions CI/CD.

2. Docker, Kubernetes (AKS), Helm.

3. Terraform or Bicep for infrastructure automation.

- Experience managing production roll-outs, blue-green deployments, and canary releases.

Real-Time & Scalable UI :

- Knowledge of WebSockets/SSE, state management, and high-performance UI rendering.

Testing & Observability :

- Experience with automated unit/E2E testing.

- Strong knowledge of logging, tracing, monitoring (App Insights, Log Analytics), and alerting.