HCLTech
AI Solutions Architect
Skills
17 days ago
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Important information
Contract type:
Permanent
Location:
London, UK
Work mode:
Onsite
Published on:
8 October 2026
What they need
Key Responsibilities
- Lead the architecture, design, and development of enterprise-scale web applications with integrated Generative AI capabilities.
- Define technical standards, architectural patterns, and best practices for scalable and secure software systems.
- Collaborate with product, AI/ML, DevOps, and security teams to ensure alignment between business goals and technical execution.
- Oversee full-stack development lifecycle, ensuring robust design, performance tuning, and security compliance.
- Evaluate and integrate AI components such as LLMs, embedding services, and vector databases into product architecture.
Mandatory Technical Skills
- Cloud-Native Architecture & Microservices
- Proven experience designing scalable, cloud-native applications using microservices and event-driven patterns on Azure Ecosystem.
- Performance Optimization
Implementing caching strategies (Redis, CDN), asynchronous job processing (RabbitMQ, Kafka), and load-balanced architectures using Kubernetes or serverless platforms.
- GenAI Integration & LLM Orchestration
- Hands-on with Generative AI technologies—Azure OpenAI, prompt engineering, RAG pipelines, embeddings, and vector search (e.g., Azure AI search, Azure PostgreSQL etc..).
- Backend Engineering (APIs, Data, Security)
- Strong expertise in REST APIs with versioning, throttling, and gateway integrations., PostgreSQL/MongoDB, OAuth2/SSO, and secure coding aligned with GDPR/SOC2 standards.
- Frontend Development (React/Next.js)
- Deep experience building enterprise-grade UIs using React.JS, component libraries, and modern design systems.
- DevOps & Infrastructure as Code
- Proficiency in Azure CI/CD pipelines , Docker, and Kubernetes for automated, scalable deployments.
- Real-Time & Scalable UI Patterns
- Experience with WebSockets/SSE, UI performance optimization, and handling large-scale dynamic frontends.
Testing, Observability & Quality Engineering
Competence in automated unit/E2E testing , frontend performance profiling, and monitoring of Deployed solutions
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