Senior Software Engineer and Technical Lead, 7+ years at Visa, covering the full stack of an AI platform: the agent layer, the data and retrieval systems beneath it, and the Kubernetes and delivery infrastructure beneath that. I have built and operated each layer in production, an uncommon combination in a field where most practitioners have depth in one.
I currently lead a production LangGraph multi-agent system serving enterprise analysts - agent orchestration, retrieval architecture, natural-language querying with a validation layer over generated SQL, ingestion across 15+ sources, and trace-level evaluation of retrieval quality. Previously: self-managed Kubernetes across 900+ nodes with its networking, policy, GitOps and scheduling stack; an organisation-wide OpenSearch cluster; and self-service CI/CD and secrets platforms adopted by 50+ teams.
My judgement runs toward reliability over novelty - deterministic paths where they suffice, observability instrumented before it is needed, build-versus-buy decided on operational cost. As a lead I own architecture and interface contracts across several engineering pods, and invest heavily in mentoring. Community: contributions to CPython, pytest and Trino; co-organiser of BangPypers.
Seeking senior or staff roles in AI platform engineering, agentic systems, or platform/infrastructure engineering, where platform work is treated as a product discipline.
Remote: Yes; on-site/hybrid also works
Willing to relocate: Yes - UAE, EU, UK, ANZ, SG
Technologies: Python, Java, Spring Boot, FastAPI | LangGraph, LangSmith, MCP, RAG, NL2SQL, MLflow, Kubeflow | Kubernetes, Helm, Terraform, ArgoCD, Istio, Kyverno | MySQL, PostgreSQL/PgVector, MongoDB, ClickHouse | OpenSearch, Elasticsearch, Lucene | Prometheus, Grafana, Thanos, GitHub Actions
Résumé/CV: https://kumida.xyz/resume
Email: kayrahul@gmail.com
Senior Software Engineer and Technical Lead, 7+ years at Visa, covering the full stack of an AI platform: the agent layer, the data and retrieval systems beneath it, and the Kubernetes and delivery infrastructure beneath that. I have built and operated each layer in production, an uncommon combination in a field where most practitioners have depth in one.
I currently lead a production LangGraph multi-agent system serving enterprise analysts - agent orchestration, retrieval architecture, natural-language querying with a validation layer over generated SQL, ingestion across 15+ sources, and trace-level evaluation of retrieval quality. Previously: self-managed Kubernetes across 900+ nodes with its networking, policy, GitOps and scheduling stack; an organisation-wide OpenSearch cluster; and self-service CI/CD and secrets platforms adopted by 50+ teams.
My judgement runs toward reliability over novelty - deterministic paths where they suffice, observability instrumented before it is needed, build-versus-buy decided on operational cost. As a lead I own architecture and interface contracts across several engineering pods, and invest heavily in mentoring. Community: contributions to CPython, pytest and Trino; co-organiser of BangPypers.
Seeking senior or staff roles in AI platform engineering, agentic systems, or platform/infrastructure engineering, where platform work is treated as a product discipline.