
Backend & systems engineer | Java . Rust · Go · Cloud-native | ML infra & AI backends | Clean architecture, high-performance systems.
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Assessing your cultural and operational fit
Tech9
Frontend Developer
June 21, 2026 – Present
rust-ai-gateway
May 31, 2026 – Present
⚡ Production-grade Distributed AI Gateway built in Rust — Multi-provider routing (OpenAI +Claude+ Ollama), auth, rate limiting, usage tracking, Prometheus metrics, Grafana dashboards, Docker + AWS deployment
View Projectai-gateway
May 25, 2026 – Present
A unified API gateway for multiple LLM providers (OpenAI, Anthropic, and more) with built-in resilience, caching, observability, and hot-reloadable configuration.
View Projectchatbot
May 19, 2026 – Present
Production-oriented Rust backend project for multi-provider AI chat.
View Projectsentinel-proxy
May 18, 2026 – Present
A small Rust reverse proxy with round-robin upstream routing, request stats, and a health endpoint.
View Projecthttp-load-tester
May 17, 2026 – Present
An async HTTP load testing CLI written in Rust with Tokio and reqwest. It sends a configurable number of requests to a target URL, caps concurrent in-flight work, and prints throughput, latency percentiles, status-code counts, and error summaries.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards backend, system-level programming, and AI/ML infrastructure, primarily using Rust. While this demonstrates strong technical depth, the target role is 'Frontend Developer'. This creates a significant mismatch in primary skill focus. The candidate has some exposure to HTML, CSS, and JavaScript in projects like 'NetSentinel' and 'MihirMohapatra.github.io', but these appear to be secondary to the core Rust backend work. The diversity of projects is high in terms of complexity and domain (AI, networking, security), but not in terms of frontend-specific technologies or frameworks relevant to a dedicated frontend role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are technically focused, and no psychometric or English test results are available.