Security Engineer – AI/ML/DevSecOps / Application Security

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Position Summary

We are seeking a Security Engineer – AI/ML/DevSecOps / Application Security with strong hands-on delivery experience in

SAST, SCA, and DAST to embed security across the software development lifecycle. This role focuses on implementing and

operating application security tooling in CI/CD pipelines, executing application security assessments (including API security),

triaging and prioritizing findings, enabling remediation, and driving secure-by-design engineering practices across cloud-native

and enterprise applications. SAST, SCA, and DAST remain foundational AppSec capabilities, and the role is positioned

accordingly with an emphasis on measurable delivery outcomes (tool onboarding, pipeline coverage, risk reduction, and

remediation closure).

As a Security Engineer, you will:

∙Integrate, configure, and optimize SAST, SCA, and DAST tools within CI/CD pipelines to automate security testing

across build, test, and release stages (including quality gates and exception workflows).

∙Perform static, dynamic, and open-source dependency assessments to identify vulnerabilities including OWASP Top

10 risks, insecure libraries, exposed secrets, misconfigurations, and software supply-chain weaknesses.

∙Execute API security testing (REST/GraphQL) including authentication/authorization validation

(OAuth2/OIDC/JWT), input validation, rate limiting/abuse cases, and broken object/function level authorization

(BOLA/BFLA), and translate results into developer-ready fixes.

∙Analyze scan results, remove false positives, prioritize findings based on exploitability and business impact, and

provide clear, actionable remediation guidance (secure coding patterns, compensating controls, and verification steps).

∙Work hands-on with developers, DevOps engineers, architects, and client stakeholders to embed secure coding, secure

design, and shift-left security practices, including playbooks, office hours, and remediation sprints.

∙Support threat modeling and security design reviews; convert threats into actionable security requirements, test cases,

and engineering backlog items aligned to delivery timelines.

∙Track vulnerabilities through closure, validate remediation (re-scan, proof of fix, and regression checks), and ensure

issues are managed in line with client policy, risk tolerance, and SLA expectations.

∙Implement additional DevSecOps controls such as IaC scanning, secrets detection, container image scanning, and

Kubernetes security checks (where applicable), including policy-as-code to prevent insecure deployments.

∙Strengthen software supply-chain security by supporting SBOM generation/consumption, dependency hygiene, and

build/release integrity controls (e.g., artifact signing/verification and provenance where applicable).

∙Automate repeatable security tasks using scripting (e.g., Python/Bash) and integrations (APIs/webhooks) to improve

scan reliability, reporting, and developer workflow adoption.

∙Design and build AI agents / agentic workflows for AppSec automation (e.g., triage, false-positive suppression, secure

code review assistance, threat-model generation, remediation assistance), ensuring appropriate guardrails, logging, and

human-in-the-loop validation.

∙Perform current-state assessments of client DevSecOps and emerging AISecOps practices against industry standards;

provide prioritized recommendations and an implementation roadmap.

∙Perform security testing across modern application surfaces—code, APIs, cloud, containers/Kubernetes—and, where

applicable, AI/ML pipelines (e.g., RAG data flows, model integration points, and tool/function calling) using a

combination of automated and manual techniques.

∙Produce security assessment reports, dashboards, trend analysis, and root-cause insights for technical and non-technical

stakeholders.

∙Contribute to secure SDLC standards aligned to recognized verification frameworks such as OWASP ASVS

∙Stay current on emerging threats, AppSec tooling trends, software supply-chain risks, and new attack surfaces

introduced by AI-enabled applications and agentic workflows.

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Requirements

Qualifications

∙Own end-to-end delivery for a workstream (or multiple applications): tool onboarding plan, scan strategy

(SAST/SCA/DAST/API), coverage tracking, and closure metrics.

∙Design and implement CI/CD security patterns at scale (reusable templates, quality gates, exception workflows),

including policy-as-code and integrations with vulnerability management/ticketing/reporting.

∙Design and build AI agents / agentic workflows for AppSec automation use cases (e.g., automated vulnerability

triage, false-positive suppression, secure code review assistance, threat-model generation, and remediation assistance),

with human validation and safe-guardrails.

∙Lead security architecture reviews, threat modeling, and risk-based prioritization with clients for modern applications,

microservices, APIs, and AI/ML systems (including LLM-based and agentic architectures); translate outcomes into