Principal Security Engineer

About the role

About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com.

The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024.

Join us in Securing Tomorrow Together!

The Role

AiDASH protects the critical infrastructure that delivers power to tens of millions of people. As we embed GenAI more deeply into our SaaS products (RAG pipelines, agentic / MCP services) and roll out AI-assisted development internally, the threat landscape is shifting fast. Autonomous adversaries, prompt injection, model exfiltration, and vibe-coded internal apps spun up by non-engineers are now part of the daily attack surface.

We're hiring a Principal Security Engineer to be our deepest technical voice on security. In the role, you'll own our AppSec program and lead AI/LLM security hardening across the platform. You'll embed security into every layer of the SDLC (from PR to production), and be the person who figures out what "secure agentic AI" actually looks like in a product that ships to critical infrastructure operators. You will report to senior leadership and work closely with Platform, ML, and DevOps across our US and India teams.

How you'll make an impact:

AppSec & DevSecOps

Own and mature the AppSec toolchain across CI/CD — SAST, DAST, SCA, secrets scanning, and IaC policy-as-code

Champion shift-left security: threat modeling and secure-design reviews embedded in PRs and sprint planning, not bolted on at release

Run SBOM/AIBOM tooling; enforce risk-tiered dependency controls; extend SLSA practices to model artifacts

Write and enforce IaC policy-as-code (OPA/Rego, Checkov, Kyverno, or equivalent) in live pipelines

AI & LLM Security

Harden production GenAI deployments on AWS (managed model APIs, agentic/MCP services) — IAM, VPC routing, prompt-layer guardrails, output filtering, rate and cost controls

Codify OWASP LLM Top 10 and MITRE ATLAS controls into the SDLC; introduce LLM eval-as-gate in CI

Govern internal AI-assisted developer tooling — DLP for what egresses to external model providers, sensitive-data discovery in prompts, acceptable-use telemetry

Stand up controls for shadow AI and vibe-coded apps: discover, classify, gate with sane defaults, and bring under the SDLC

Cloud Security (AWS)

Harden AWS posture across accounts — Organizations, SCPs, Control Tower — and mature Kubernetes security (admission controllers, runtime visibility)

Operate CSPM/CNAPP tooling; own vulnerability management across containers and IaC

Support zero-trust privileged access for production infra, databases, and Kubernetes (in partnership with DevOps)

Compliance Support

Support the company’s path to ISO 27001 and ISO 42001 certifications in 2027 — gap assessments, control sets, evidence pipeline

Maintain SOC 2 Type II posture in partnership with the compliance team

Translate emerging AI regulation (EU AI Act, NIST AI RMF, utility-sector mandates) into concrete engineering requirements

What we're looking for:

Minimum Qualifications

10+ years in security engineering with meaningful AppSec depth — you have shipped and operated SAST/DAST/SCA (Semgrep, CodeQL, Snyk, Veracode, or equivalent) at production scale

Hands-on experience securing production LLM or agentic AI deployments — IAM, guardrails, prompt injection controls, eval gating. RAG-demo experience alone does not meet the bar

Cloud-native security experience in AWS — comfortable with Organizations/SCPs, Kubernetes security, container hardening, and CSPM tooling

IaC policy-as-code in a live pipeline (OPA/Rego, Checkov, Kyverno, tfsec, or equivalent)

SBOM/AIBOM tooling at production scale (Interlynk, Anchore, Dependency-Track, or equivalent)

Compliance fluency: has personally contributed to a SOC 2 Type II or ISO 27001 audit — can read a control map without flinching

SF Bay Area based; able to work hybrid (2 days/week in Palo Alto)

Preferred Qualifications

Hands-on MCP work — design, hardening, or auth — even early-stage

LLM eval-as-gate in CI (Promptfoo, Garak, DeepEval, Giskard) and AI red-teaming experience

Prompt-layer DLP and AI runtime guardrails (Nightfall, Lakera Guard, Cyberhaven, Harmonic Security, Protect AI, NVIDIA NeMo Guardrails)

ISO 42001 familiarity; NIST AI RMF and EU AI Act high-risk system requirements

Experience securing SaaS sold into regulated sectors (utilities, energy, financial services, healthcare)

EDR/XDR operations experience (CrowdStrike, SentinelOne, Defender) — helpful but not the primary focus of this role

Comfort working across US/India time zones with a distributed team

Public signals: conference talks, open-source contributions in CI/CD, MCP, or LLM-deployment security

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.
We are committed to providing an inclusive and accessible interview experience for all candidates. Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs. Read our Privacy Policy here: https://www.aidash.com/policy/privacy-policy/