Morgan Stanley (via Wissen) · SE II · Agentic SDLC for 6 teams · Snowflake Cortex
I build production backend systems and data pipelines — with agentic AI where it earns its place.
Technologies I work with
With 2+ years building production enterprise systems, I focus on backend architecture and data engineering — resilient distributed services beyond basic API wrappers.
My specialty sits at high-volume data processing and autonomous systems: ETL pipelines, optimized data streams, and Agentic AI for intelligent decision-making at scale.
"Great engineering should feel invisible. I build heavy-lifting systems behind the scenes so that complex data and intelligent workflows can just... work."
System Design Snapshot — PnLGuard
Ingest → Rule Engine → PostgreSQL Store → GenAI Explainer → HITL Review → Audit Store
Rules stay deterministic; GenAI adds context for human reviewers.
Resilient microservices and distributed systems with Spring Boot.
Fault-tolerant ETL, query optimization, and distributed processing.
LLM and agent workflows integrated into production systems.
Idempotency, caching, and resilient data flows at scale.
Backend-led end-to-end features — Spring Boot APIs with React or Angular frontends.
Docker, AWS, and CI/CD for reliable deployment and production ops.
AI-driven platforms for backend reliability, data pipelines, and distributed systems.
Detect breaking OpenAPI changes, score deployment risk, and enforce governance via CLI, GitHub Actions, and PR comments.
Live on npm & GitHub Marketplace — drop into any CI pipeline
Rule + AI anomaly detection on P&L feeds with HITL review and audit trail.
Offline-first pregnancy companion — local journaling, milestones, memory export. Live on Google Play.
Private repository — Live on Google Play — proprietary source, private repository.
Multi-tenant GenAI backend: RAG, personas, key rotation, Telegram + Web.
Notes on distributed systems, idempotency, and production backends.
Mar 2026
How in-memory caching stabilized P99 latency through a 70% traffic spike.
Apr 2026
APIs that survive network partitions, retries, and duplicate concurrent requests.
Jun 2026
A deep dive into the hidden complexities of natural language interfaces for databases.
From full-stack roots to backend systems, data pipelines, and agentic workflows at scale.
Wissen Technology (Client: Morgan Stanley)
Wissen Technology (Client: Morgan Stanley)
Wissen Technology (Client: Morgan Stanley)
"Ashirvad is the kind of backend engineer you trust with your most critical systems. He picks up unfamiliar tech stacks incredibly fast, immediately contributing production-ready code. When he owns a service, I know it will be delivered robustly with zero handholding."
Have an interesting backend, data, or AI platform challenge? I'd love to hear from you.
Focus: Backend systems, data pipelines, agentic AI platformsBased in: Bengaluru — happy to connect remotelyBest for: Architecture discussions, OSS, product feedback, and selective side builds
