
Required Qualifications Experience
10+ years in Solution/Enterprise Architecture/ Software Engineering
5+ years experience as a Lead/Senior architect or senior technical lead for large IT projects spanning multiple enterprise systems
2+ years of hands-on AI development and deployment
Proven experience delivering production-grade AI products
Strong track record in cloud modernization and migration initiative
Key knowledge of all Software Development Life Cycle (SDLC) activities, including ideation, design, implementation, validation of functional and non-functional aspects, and Day 2 operations.
Knowledge and experience with enterprise architecture pattern development, cloud-native architecture, and agile delivery.
Experience with enterprise-grade technical integrations involving a variety of modern technical capabilities
Core Technical Skills
Strong hands-on expertise in: Agentic AI frameworks (MCP, ADK, Lang Graph, Lang Chain), LLM integration & orchestration, RAG (Retrieval-Augmented Generation) systems
Experience with Vector databases (Pinecone, FAISS, Weaviate, etc.) and Graph databases (Neo4j, Neptune, etc.)
Strong knowledge of: Semantic search, embeddings, knowledge graphs.
Multi-agent systems and workflow orchestration
Deep experience with: Google Cloud Platform (preferred): Vertex AI, Cloud Run, GKE, Azure
Strong background in: API design, microservices, distributed systems.
Backend development (Python preferred)
Experience implementing: AI/ML pipelines (CI/CD), Model and prompt lifecycle management, Monitoring and evaluation frameworks
Strong understanding of Responsible AI, Governance, security, and compliance
Experience building AI-driven interfaces using: ReactJS, Flask, or similar frameworks
Experience in AI governance, compliance, and data security frameworks
Exposure to multi-modal or autonomous agent ecosystems(preferred)Soft Skills
Strong communication and stakeholder management skills
Ability to lead cross-functional teams and influence decisions
Strategic thinking with strong execution focus