Platform, DevOps, AI Automation, and Backend Engineer
I build production-shaped systems that connect automation, cloud infrastructure, APIs, operational intelligence, and reliable software delivery. My portfolio focuses on measurable outcomes: repeatable workflows, safer deployments, observable services, tested APIs, and maintainable delivery practices.
| Project | Engineering focus | Evidence |
|---|---|---|
| AI Delivery Enablement Control Plane | Governed workflow automation, operational KPIs, cost and capacity reporting | Production release, 92%+ coverage, CI, CodeQL, multi-architecture container |
| Zero Outage DevOps | Secret validation, deployment gates, Terraform, Docker, AWS delivery patterns | Tested Node 24 container, successful CI, public release |
| RL Gym FastAPI Platform | Typed APIs for RL simulation, benchmarking, and policy evaluation | Seven tests, linting, CI, AMD64/ARM64 container |
| Agent Conversation Data Studio | Tool-calling conversation generation and validation | Python, JavaScript, Java, CI, public API container |
| LLM Code Evaluation Lab | Multi-language review of AI-generated code, tests, and fixes | Python, JavaScript, Java, Go, Rust, C++, verified CI |
| AWS DevOps Platform | Containerized health service, Terraform scaffolding, AWS delivery reference | CI validation and public multi-architecture container |
Platform & DevOps Docker · GitHub Actions · Terraform · AWS · Kubernetes patterns
Backend Engineering Python · FastAPI · REST APIs · SQLAlchemy · Node.js
AI Engineering LLM evaluation · Tool calling · Synthetic data · RL workflows
Operational Systems Automation governance · KPIs · Reliability · Runbooks · Cost visibility
Quality & Security Pytest · Ruff · CodeQL · CI gates · SBOM · Provenance attestations
- Versioned GitHub Releases across automation, cloud, backend, AI, analytics, and RevOps work.
- Public GitHub Container Registry images for tested runnable services.
- AMD64 and ARM64 images with SBOM and build-provenance attestations.
- Explicit open-source licenses and client-ready setup documentation.
Explore:
- Define the operational problem and measurable target.
- Build the smallest repeatable service or workflow that proves value.
- Add tests, security checks, observability, documentation, and rollback paths.
- Package the result so another engineer can run and evaluate it consistently.
- Separate portfolio demonstrations from claims of real client production usage.
Based in India. Open to platform engineering, DevOps, backend, cloud automation, and AI enablement opportunities.