AI Architect

Job Summary

We are seeking a highly skilled and hands-on AI Solution Architect to lead the design, architecture, and implementation of enterprise-scale AI and AIOps platforms. The ideal candidate should be capable of understanding complex business and operational requirements, translating them into scalable AI architectures, and actively contributing to development and implementation activities across AI, backend, cloud, orchestration, and data platforms.

This role requires a strong combination of architecture leadership, AI engineering expertise, cloud-native solutioning, and hands-on development experience with modern AI/LLM ecosystems.

Key Responsibilities

• Understand business, operational, and technical requirements and convert them into scalable AI solution architectures
• Design enterprise-grade AI/AIOps architecture including orchestration layers, agentic AI frameworks, RAG pipelines, vector search, and MCP integrations
• Lead architecture and technical discussions with client stakeholders, enterprise architects, and operational teams
• Design scalable plug-and-play AI agent frameworks for future extensibility
• Define AI governance, security, caching, and LLM cost optimization strategies
• Develop hands-on solutions using Java Spring Boot, Angular, Vertex AI/Gemini, Big Query, and cloud-native services
• Design and implement AI orchestration frameworks, Context Managers, tool calling, and multi-agent workflows
• Build and optimize RAG pipelines, embeddings strategies, vector search, and knowledge graph integrations
• Design secure enterprise integration patterns for Service Now, CMDB, observability platforms, and operational systems
• Implement caching, SQL-first routing, prompt optimization, and token management strategies for AI cost optimization
• Guide DevOps, CI/CD, observability, and production deployment strategies for AI workloads
• Participate in hands-on coding, code reviews, technical troubleshooting, and performance optimization
• Provide technical leadership and mentoring to development teams

Skill Requirements

AI / LLM / Agentic AI

• Vertex AI / Gemini
• Agentic AI architecture
• MCP (Model Context Protocol)
• RAG architecture
• Vector databases / vector search
• Embeddings and semantic search
• Prompt engineering and optimization
• AI orchestration frameworks
• Multi-agent workflows
• Context management strategies
• AI governance and guardrails

⸻

Backend & API Development:

• Java Spring Boot
• REST APIs / Microservices
• Security frameworks (OAuth2, JWT, RBAC)
• API Gateway integration
• Caching frameworks (Redis/Caffeine)⸻

Cloud & Data Platforms:

• Google Cloud Platform (GCP)
• Big Query

Required Experience:

• 15+ years overall IT experience
• 4+ years in AI/ML/LLM solution architecture
• Experience designing enterprise AI/AIOps platforms
• Strong hands-on coding and implementation experience
• Experience with cloud-native AI solutions on GCP preferred
• Experience with healthcare, operational platforms, or enterprise IT operations preferred

Other Requirements

1. Optional But Valuable: Certifications In Machine Learning (E.G., Tensorflow Developer Certificate, Aws Certified Machine Learning Specialty, Or Similar).