ai automation engineer at dashrai los angeles ca

The Mission

Dashr.ai is an AI-powered security compliance platform built by security practitioners. We're hiring an AI Automation Engineer with one mandate: automate and agentize everything we do — from risk assessment to security monitoring to compliance evidence workflows — so a small expert team delivers like a large one.

You do NOT need to be a cybersecurity expert. Our founder supplies the security domain knowledge and requirements; you turn them into working, reliable, documented automations. If you're a strong AI/automation engineer who learns unfamiliar domains fast and asks sharp questions, this role was designed for you.

This is a builder role, not a research role. You'll ship working agents and automations against defined acceptance criteria, starting with a paid proof-of-concept engagement.

What You'll Do

- Translate security processes described by our founder into AI agents and automation pipelines — starting with security monitoring, evidence collection, KPI reporting, and risk-assessment workflows<br/>- Build reliable LLM workflows: prompt pipelines, structured outputs, tool/function calling, retrieval, guardrails, and evaluation harnesses<br/>- Integrate with our operational stack via APIs: SentinelOne, Wazuh, NinjaOne, Microsoft 365 / Entra ID, Azure and AWS<br/>- Instrument everything: logging, error handling, human-in-the-loop checkpoints where accuracy matters (compliance evidence cannot hallucinate)<br/>- Document each automation so it encodes the domain knowledge behind it and is maintainable, auditable, and hand-off ready<br/>- Extract requirements like a consultant: ask the questions that turn a messy verbal process description into a precise specification

Must-Haves

1. Have you personally built and shipped a production LLM-powered automation or agent (not a demo or tutorial project)? (Y/N)<br/>2. Do you have 3+ years hands-on Python (or TypeScript) building API integrations and automation pipelines? (Y/N)<br/>3. Have you built automations or integrations against third-party APIs in a production environment? (Y/N)

Strongly Preferred

- Software engineering fundamentals: testing, version control, CI, code review discipline — code that survives a second client, not just a demo<br/>- Experience making LLM outputs verifiable — evals, structured validation, citation of source evidence<br/>- Agent frameworks and orchestration patterns (function calling, multi-step tool use, eval-driven development)<br/>- Azure automation depth (Logic Apps, Functions, Graph API); AWS equivalent welcome<br/>- Any exposure to security or IT tooling (SIEM, EDR, RMM) or compliance frameworks (ISO 27001, SOC 2) — helpful, not required

How We Work

- Deliverable-based contracts with defined acceptance criteria — outcomes, not hours<br/>- Async-first, multi-workstream environment; you manage your own execution<br/>- Direct collaboration with the founder as your domain expert and requirements source<br/>- Contract-to-hire: strong POC delivery converts to a larger ongoing role with an expanding automation roadmap

Hiring Process

1. Predictive Index two-part assessment: behavioral (~10 min, untimed) + cognitive (12 min, timed)<br/>2. Hands-on technical exercise (50% of decision weight)<br/>3. Structured interview (30%)<br/>4. Decision within days, not weeks

Note on IP and Scope

All engagements begin with an IP assignment agreement before any code access is granted. Certain workstreams — including automation of our proprietary penetration-testing methodology — begin only after IP assignment is fully executed. The technical exercise uses neutral scenarios; no proprietary systems or prior security knowledge required.

Location: Los Angeles, CA (Remote)

Remote: Yes