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AI Security & Platform Engineer

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AI Security & Platform Engineer in Others

  • Metaforms
  • Full time
  • Email
  • Bengaluru, India

Responsibilities

  • Adversarially test AI agents for prompt injection, context poisoning, unsafe tool use, data leakage, memory manipulation, and unintended behavior.
  • Threat-model AI features, agent workflows, model integrations, and tool-calling capabilities, and build repeatable adversarial evaluations and regression tests.
  • Design controls for least-privilege tool access, scoped credentials, sandboxing, runtime policy enforcement, human approval, output validation, and agent containment.
  • Review customer-facing applications and APIs for authentication, authorization, tenant isolation, injection, and business-logic vulnerabilities.
  • Reproduce security reports, assess real-world impact, perform focused code reviews and penetration tests, and implement production-ready fixes.
  • Harden cloud permissions, service identities, secrets, storage, networking, deployment pipelines, and production access.
  • Build security guardrails, observability, model-provider routing, rate limits, cost controls, kill switches, and incident investigation capabilities.
  • Work directly with engineers and engineering leadership to develop reusable security patterns and take ownership of larger AI security and platform initiatives.

Requirements

  • 2–3 years of hands-on experience across AI engineering, backend/platform engineering, application security, infrastructure security, DevSecOps, or a related engineering role.
  • Experience building, operating, or securing production AI systems using LLM APIs, agents, tool calling, RAG, model gateways, or similar technologies.
  • Strong programming ability in Python, TypeScript, Go, or another relevant language.
  • Understanding of web and API security risks including authentication, authorization, injection, tenant isolation, secrets, and unsafe data handling.
  • Practical experience with cloud infrastructure, CI/CD, containers, monitoring, or infrastructure-as-code.
  • Ability to investigate, reproduce, and assess vulnerabilities and contribute effective fixes.
  • Ability to reason about trust boundaries between users, models, customer data, application code, tools, and third-party services.
  • Comfort debugging through source code, logs, traces, metrics, and database queries.
  • Strong written communication and ability to explain security risks clearly.
  • Preferred experience includes AI red teaming, adversarial model testing, prompt injection, agent sandboxing, multi-tenant SaaS security, OAuth, webhooks, file processing, MCP, security test harnesses, fuzzers, automated evaluations, SAST, DAST, dependency scanning, secret scanning, infrastructure scanning, model gateways, AI observability, LLM evaluations, bug bounties, CTFs, security research, or relevant open-source projects.
  • Familiarity with SOC 2 or ISO 27001 from an engineering implementation perspective is preferred.

Benefits

  • Work on practical AI-security problems in production agent systems.
  • Operate across offensive testing, application security, and platform engineering while shipping fixes and controls directly.
  • Work closely with engineering leadership and influence platform design early.
  • Take meaningful ownership while developing an emerging technical specialization.
  • The hiring process includes an introductory conversation, technical discussion, practical agent-security exercise, and final conversation with engineering leadership.

Metaforms

Metaforms builds an AI‑agent research operations platform that speeds up survey design, programming, testing, data cleaning/coding, tabulation, and reporting for market research agencies and in‑house insights teams. It sells a SaaS workflow that plugs into tools such as Qualtrics, Confirmit, Deci...

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