Distributed Task Processing Platform
Production asynchronous processing system with chunking, parallel consumers, idempotency, Redis locking, retries, dead-letter handling, and status tracking.
C#/.NET · Event-driven systems · Production AI
Building scalable backend systems with C#/.NET, event-driven architectures, distributed processing, and production AI.
Selected Professional Work
These case studies describe my contributions and general engineering decisions. The systems and source code are company-owned and private.
Production asynchronous processing system with chunking, parallel consumers, idempotency, Redis locking, retries, dead-letter handling, and status tracking.
Recruitment matching system that demonstrates embedding space, vector similarity, organization isolation, metadata filtering, and result ranking.
Production AI recruitment agent with conversation state, intent detection, tool invocation, retrieval, structured responses, and hallucination controls.
Experience
Production experience across event-driven processing, high-volume asynchronous workflows, recruiter-facing backend APIs, and applied AI systems.
Distributed processing, high-volume pipelines, and AI systems.
Multi-tenant event-driven processing using C#/.NET, RabbitMQ, MassTransit, and workers, supporting parallel execution across 10+ enterprise tenants.
Saga-style asynchronous pipelines with request batching, chunk queues, Redis distributed locking, MySQL state, retries, requeues, recovery, and completion tracking.
Production experience with text agents, voice agents, RAG, structured outputs, tool calling, embeddings, and vector search.
Recruitment workflow orchestration, backend APIs, candidate discovery, and automation.
Built and evolved backend services that coordinate recruiter-facing workflows, API integrations, candidate operations, and system automations.
Worked on backend experiences that support candidate search, filtering, ranking, and operational visibility for recruitment workflows.
Focused on queue behavior, service boundaries, state visibility, safe retries, and operational patterns that keep backend workflows observable and recoverable.
Engineering Articles
Short technical write-ups on backend decisions that usually matter after the happy path: idempotency, locks, retries, throughput, and ranking.
Deduplication keys, state transitions, replay safety, and exactly-once expectations.
Lock ownership, expiry, contention, and recovery when workers disappear.
Failure classification and how retry policies protect throughput.
About
Rishabh is a C#/.NET backend engineer with 4 years of experience building distributed, event-driven systems and production AI-powered applications.
Resume
Senior Software Engineer with 4 years of experience building scalable backend and distributed systems using C#/.NET, event-driven architectures, asynchronous processing, and production Agentic AI applications.
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Hiring for backend, distributed systems, .NET, or production AI engineering? Reach me directly.