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AI Security Engineer

Remote / Online - Candidates ideally in
Seattle, King County, Washington, 98127, USA
Listing for: DocuSign, Inc.
Part Time, Remote/Work from Home position
Listed on 2025-12-20
Job specializations:
  • IT/Tech
    AI Engineer
Job Description & How to Apply Below

Company Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business‑critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity.

Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e‑signature and contract lifecycle management (CLM).

What you’ll do

We are seeking a talented and creative AI Security Automation Engineer to join our team. In this role, you will be responsible for designing, building, and deploying AI Agents and custom AI‑powered tooling that empower the Security organization to work faster and more effectively. You will leverage cutting‑edge technologies, such as Glean, Crew.

AI, and cloud‑native AI services on Azure and AWS, to automate complex security workflows. You will collaborate closely with security teams (Detection & Response, GRC, Product Security) to identify bottlenecks and engineer AI solutions that reduce manual toil, accelerate response times for customers and employees, and streamline security operations.

This position is an independent contributor role reporting to the Sr Director of AI & Data Security.

Responsibility
  • Design and implement autonomous AI Agents and multi‑agent systems (using frameworks like Crew.

    AI or Lang Chain) to automate repetitive security tasks and workflows
  • Integrate and optimize new third‑party AI‑powered security solutions, ensuring seamless interoperability with existing security infrastructure
  • Integrate enterprise AI search and knowledge retrieval tools (e.g., Glean) into security operations to accelerate information discovery and decision‑making
  • Develop and maintain custom AI/ML tooling on cloud platforms (AWS, Azure) to support internal security use cases
  • Collaborate with security team members to identify high‑impact opportunities for AI automation, such as automated ticket triage, vendor risk analysis, or vulnerability prioritization
  • Ensure all developed AI tools and agents adhere to internal security standards, data privacy requirements, and governance guardrails
  • Monitor the performance and reliability of deployed AI agents, continuously optimizing them for accuracy and efficiency
  • Stay current with the rapidly evolving landscape of AI engineering, Agentic workflows, and LLM capabilities to bring new innovations to the team
  • Translate technical capabilities of AI tools into tangible business value for the security organization
Job Designation

Hybrid:
Employee divides their time between in‑office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in‑office expectation)

Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position’s job designation depending on business needs and as permitted by local law.

What you bring Basic
  • 5+ years of experience in software engineering, Dev Ops, or security engineering, with a strong focus on automation and tooling
  • Proficiency in Python and experience building applications with LLM frameworks (e.g., Lang Chain, Crew.

    AI, Semantic Kernel)
  • Experience designing and deploying AI Agents or Chatbots that interact with external APIs and data sources
  • Hands‑on experience with cloud platforms (AWS, Azure, GCP) and serverless architecture (Lambda, Azure Functions)
  • Experience with Vector Databases and RAG (Retrieval‑Augmented Generation) architectures (e.g., utilizing Glean, Pinecone, or Azure AI Search)
  • Strong understanding of software development life cycles (SDLC), CI/CD pipelines, and version control (Git)
  • Familiarity with security concepts and workflows (SOC, Vulnerability Management, GRC) to effectively partner with security…
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