About the Role
Nanoprecise Sci Corp is building the security spine of a next-generation IoT + AI platform used across industrial and enterprise environments. We are looking for a seasoned Security Engineer who combines deep technical offensive and defensive expertise with the ability to architect, automate, and scale security programs across firmware, cloud, AI systems, and wireless infrastructure.
You will own the security posture of our embedded hardware, CI/CD pipelines, AI implementations, and network perimeter — with a mandate to shift security left, operationalize threat intelligence, and mentor a growing team.

Key Responsibilities

AI Security
Design and enforce security controls for all internal and external AI/LLM deployments
Conduct threat modeling on AI pipelines using MITRE ATLAS and STRIDE frameworks
Implement prompt injection defenses, output filtering, and AI audit logging
Lead shadow AI discovery programs and define acceptable use policies
Perform red teaming exercises against AI models and RAG systems

DevSecOps
Own the end-to-end security of CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins)
Integrate SAST (Semgrep, CodeQL), DAST (OWASP ZAP, Burp Suite), SCA (Snyk, Dependabot), and secrets scanning (TruffleHog, Gitleaks)
Implement policy-as-code using OPA/Gatekeeper for Kubernetes and IaC environments
Establish container security standards: image signing (Cosign/Notary), runtime policy (Falco), RBAC hardening
Drive developer security training and threat modeling in sprint planning

Firmware Reverse Engineering & Embedded Security
Lead firmware security assessments on IoT and edge devices using Ghidra, IDA Pro, Binwalk, Radare2
Design and enforce secure firmware development lifecycle: signed OTA, secure boot, encrypted comms
Develop and maintain UART/JTAG/SPI flash extraction capabilities




Perform vulnerability research on embedded Linux, RTOS, and bare-metal firmware
Produce actionable firmware security findings with CVSS-scored remediation roadmaps

Wireless & Network Security
Conduct WiFi penetration tests across enterprise WPA2/WPA3, 802.1X, and guest network segments
Assess IoT wireless protocols: BLE, Zigbee, LoRa, Z-Wave for security weaknesses
Deploy and tune Wireless Intrusion Detection Systems (WIDS)
Develop wireless hardening standards and migration roadmaps (e.g., PSK → 802.1X)
Investigate rogue AP incidents, PMKID captures, and deauthentication attacks

Security Architecture & Operations
Design Zero Trust network architecture with microsegmentation and identity-aware access
Own SIEM integration (Splunk, Elastic, Sentinel) and threat intelligence operationalization
Lead incident response for security events across firmware, cloud, AI, and wireless layers
Produce executive-level risk reports translating technical findings into business impact

Required Qualifications & Domain Expertise
3+ years in security engineering, with demonstrable expertise across at least 3 of the 4 core domains (AI security, DevSecOps, firmware RE, wireless pentesting)
Deep hands-on experience with firmware analysis toolchains: Ghidra, IDA Pro, Binwalk, Firmwalker, QEMU/Firmadyne
Proven WiFi/wireless pentesting skills: Aircrack-ng, Kismet, Bettercap, Hostapd, Wireshark, HCXTOOLS
Strong DevSecOps pipeline experience:



SAST/DAST/SCA integration, secrets management, IaC security
Experience securing AI/ML systems and LLM-powered applications in production environments
Familiarity with MITRE ATT&CK;, MITRE ATLAS, OWASP LLM Top 10, NIST AI RMF
Strong scripting skills: Python, Bash; familiarity with Go or Rust is a plus
Relevant certifications preferred: OSCP, OSWP, GREM, GWAPT, CKS, or equivalent

Why This Role Matters
This role will define how our organization secures AI-powered products from chip to cloud. You will directly influence the security architecture of devices deployed in critical industrial environments, protect AI systems used by thousands of enterprise users, and build the DevSecOps culture that enables us to ship secure software fast.
Your work will prevent breaches, protect customer data, and ensure our AI implementations remain trustworthy, auditable, and resilient against emerging threats.

KPIs for the Role
DevSecOps & Pipeline Security (35%)
100% of production pipelines with full security gate coverage within 6 months
MTTR for critical pipeline vulnerabilities Zero high-severity secrets leak incidents per quarter

AI Security (35%)
AI security assessment coverage: 100% of production AI systems assessed within first 90 days
Shadow AI discovery: Prompt injection detection rate: > 95% of known attack patterns blocked

Firmware & Hardware Security (20%)
100% of recent device firmware reviewed before production deployment
Mean time to patch firmware CVEs: Secure boot and OTA signing coverage: > 95% of deployed device fleet

Wireless Security (10%)
100% of enterprise WiFi migrated to WPA3/802.1X within 12 months
Rogue AP mean time to detection and containment: Wireless security assessment: 100% of new sites assessed before go-live

📌 Security Engineer (Noida)
🏢 Nanoprecise Sci
📍 Noida