Dharmendra K.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

I build production-grade distributed systems, event-driven platforms, AI-enabled applications, and backend infrastructure that can scale beyond the prototype stage. With 13+ years of software engineering experience, my background spans high-volume messaging platforms, asynchronous architectures, SaaS communication systems, backend APIs, observability, reliability engineering, and modern AI application development. Most AI projects fail not because of the model, but because of poor system architecture, weak operational design, and fragile integrations. My focus is building AI-enabled systems that remain maintainable, observable, and reliable in production. 🚀 WHAT I BUILD ### Distributed Systems & Backend Platforms I design and build backend services that handle asynchronous workloads, messaging pipelines, API integrations, retries, idempotency, observability, and operational scalability. Examples include: • Event-driven architectures using Kafka and queue-based processing • High-throughput messaging and communication platforms • Microservices and API ecosystems • Reliability and observability improvements • Backend modernization and platform evolution initiatives --- ### RAG (Retrieval-Augmented Generation) Systems I build retrieval systems that combine vector search, document retrieval, orchestration logic, and LLM generation. Recent work includes OmniRAG, an open-source RAG platform built in Go featuring: • ChromaDB, Qdrant, Pinecone, and MongoDB backends • Claude and Ollama integration • Retrieval orchestration and routing • PDF ingestion pipelines • Streaming retrieval workflows • Vector database evaluation and benchmarking --- ### Agentic AI & MCP Systems I build agent-based systems that can discover tools, execute workflows, and interact with external systems. Recent work includes: • MCP-powered agents • ReAct-style agent architectures • Tool discovery and execution frameworks • Document search and retrieval agents • Database-integrated agent workflows • Claude and Ollama powered agent systems --- ### AI-Native Engineering Workflows I actively use AI-assisted engineering workflows for: • Architecture design • Development acceleration • Code reviews • Migration planning • Debugging and root-cause analysis • Operational investigations • Documentation generation My focus is practical engineering productivity rather than AI hype. --- 🛠 TECHNOLOGIES Languages: • Golang • NodeJS • PHP Backend & Infrastructure: • Kafka • Redis • MongoDB • ClickHouse • Kubernetes • Docker • REST APIs • Microservices AI & Retrieval: • Claude Anthropic | Codex | Antigravity • Ollama • MCP • RAG • ChromaDB • Qdrant • Pinecone • Chunking | Embeddings • Agent Architectures Observability & Operations: • Datadog • Grafana • Logging • Metrics • Distributed Tracing • Reliability Engineering --- 💡 WHY CLIENTS WORK WITH ME You're not hiring a prompt engineer. You're hiring an engineer who understands how production systems behave under load, how distributed systems fail, how to build reliable backend architectures, and how to integrate modern AI capabilities into real applications. Whether you're building a scalable backend platform, a RAG application, an agent workflow, or an AI-enabled product, I can help design, build, and operationalize it with a strong engineering foundation.