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:

VNETs, subnets, private endpoints, service endpoints.

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

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:

Azure DevOps or GitHub Actions CI/CD.

Docker, Kubernetes (AKS), Helm.

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.