Location: San Francisco, CA

Remote: Yes (remote or hybrid)

Willing to relocate: Yes (SF Bay Area, Seattle, NYC, Austin, other US Hubs)

Technologies: Python, DevSecOps, security engineering, security automation, threat modeling, SAST/DAST/SCA, AWS, Docker, Next.js, Node.js, OWASP LLM Top 10, AI/LLM security, CI/CD security, PostgreSQL, Hugging Face, LangChain, LLM APIs (OpenAI/Anthropic), FastAPI.

Résumé/CV: https://www.harshjannawar.com/resume | https://github.com/Harshj143

Email: hjannawar014@gmail.com

Most AI agents ship with tool access and nobody watching what they do with it. I build the enforcement layer that catches it before it becomes a breach.

Inline Proxy: open-source MCP security gateway enforcing per-tool policy (allow, block, redact, and more) on every agent tool call. Taint tracking stops a poisoned GitHub issue from publishing a repo's .env as a public gist. 194 tools covered, ~0.1ms p99, fail-closed by default.

AegisLLM: published as my master's thesis (UW 2026, ProQuest 32738510). Automated LLM red-teaming mapped to the OWASP LLM Top 10, with a genetic-algorithm engine that evolves new attack variants.

MS in Cybersecurity Engineering from UW. Top 1% on TryHackMe, with multiple CTF wins. Looking for security engineering or AI security roles at companies putting agents in production.