Rajesh 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 7, 2026.

15+ Years in Software Engineering | 🏆 Upwork Expert-Vetted | Caltech PGP in Artificial Intelligence & Machine Learning (Online) "Rajesh consistently moved swiftly from ideation to a working product, accelerating timelines and delivering great results." Rotem Alaluf, CEO of Wand.ai, valued at $150M. I design, implement, and oversee AI-native software development pipelines that turn specifications into reliable, production-ready software using AI coding agents. My expertise combines 15+ years of full-stack engineering, cloud architecture, and production systems with Claude Code, OpenAI Codex, and agent-driven software delivery. Your coding agents generate code. But can you trust what gets shipped? Your developers are using Claude Code, Codex, or other AI coding tools. Implementation is faster, but architecture consistency, code quality, testing, security, and deployment are becoming bottlenecks. I build end-to-end Agentic SDLC pipelines covering: Requirements & Planning: Specification-driven development, repository analysis, architecture reviews, technical planning, and task decomposition. Coding-Agent Orchestration: Claude Code, OpenAI Codex, Python orchestration, isolated Git branches and worktrees, and controlled agent execution. Architecture & Quality Governance: Architecture constraints, automated code reviews, independent verification, regression testing, and quality gates. Security & Human Oversight: Credential scanning, risk-based approvals, bounded repair loops, audit trails, and operator controls. CI/CD & Production Delivery: GitHub Actions, automated validation, Docker, Kubernetes, cloud deployment, release controls, and production observability. Build the pipeline. Govern the delivery. I work with engineering teams implementing AI-native development workflows and companies that need a technical architect to oversee software built primarily by coding agents. I design the engineering process, establish quality standards, review architectural decisions, and define the evidence required before software advances through testing and release. My goal isn't simply generating more code. It's creating a repeatable engineering system that produces maintainable, secure, and reliable software. Technical Expertise AI-Native Engineering: Claude Code, OpenAI Codex, MCP, Agentic SDLC, coding-agent orchestration, specification-driven development, human-in-the-loop workflows. Languages & Backend: Python, TypeScript, JavaScript, Node.js, FastAPI, REST APIs. Frontend: React, Next.js. Cloud & Infrastructure: AWS, Microsoft Azure, Google Cloud Platform (GCP), Docker, Kubernetes, Linux, CI/CD. Engineering Quality: Git, GitHub Actions, Pytest, automated testing, code review, security scanning, architecture governance, quality gates, release automation. Systems Architecture: Distributed systems, microservices, API architecture, scalability, observability, production infrastructure. Real Engineering Experience, Not Just AI Prompts I've built a Python-based Agentic SDLC orchestration system using Claude Code and Codex, covering requirements analysis, technical planning, implementation, separate verification, human approval gates, and controlled shipping. The system includes isolated Git worktrees, configurable agent execution, review and repair loops, operator controls, execution tracing, and cost tracking. A targeted automated test run passed 340 tests. I've also contributed to core product architecture and engineering at Wand.ai and CoinQuant, including an agentic AI platform serving more than 15,000 users and traders. How I Work I diagnose before I build. I work collaboratively, communicate architectural decisions clearly, and keep milestones and acceptance criteria explicit. I use Loom to explain designs, progress, and tradeoffs. I surface risks early and challenge approaches that won't hold up in production. If there's a better approach, or something isn't worth building, I'll tell you. Let's Talk If your team is adopting AI coding agents, struggling to maintain software quality, or looking to build an end-to-end AI-native development pipeline, let's discuss your engineering workflow and what needs to change.