Security Engineer for Agentic AI
Budget: $40.0 - $70.0
HOURLY / FULL_TIME
⭐ 5.00 (3)
Slovakia
oauth, python
Preferred qualifications
- Location: Europe
- Experience: Expert
The client operates at the intersection of enterprise Media Asset Management (MAM) and cutting-edge generative media. We build and scale industry-leading generative AI models, including hyper-realistic digital humans (ATMAN) and multilingual voice synthesis (VAANI), for world-class enterprise clients in entertainment, sports, healthcare, and retail.
We are looking for a Security Engineer for Agentic AI to make the agents, tools, and models the Client's teams rely on safe by default. You will own the security of Construct, our sovereign agent gateway for model routing, MCP tool hosting, and multi-agent orchestration: how agents authenticate, what they can reach, how they handle untrusted input, and how every action is logged.
This is an application and AI security role, not a cloud security role. Our Cloud Security Engineer owns GCP , Kubernetes, network, and infrastructure-as-code posture. You own the controls above it, in agents, tools, models, and their data flows, and you share secrets, sandbox runtimes, and security telemetry with them.
You work as part of a team led by the Lead Engineer for Agentic AI, together with the AI Architect , Senior Engineers, ML Engineers and Product Management. You also work closely with Security and compliance.
You own and build the security controls; the Architect designs security into the architecture, and Senior Engineers build to your standards and fix findings in their components. This is an individual contributor role: building controls, tooling, and tests, and reviewing code and designs. You also share security knowledge within the team and with other Client's teams, so safe practices spread beyond the people who build the controls. You follow emerging agent and AI threats, test new attack classes in bounded experiments, and bring proven defences into production. Once they are live, you own them: monitoring, detection, and response in an enterprise environment. We assemble our setup from open protocols, open-source components, and our own services, so you build what is missing and maintain
what you run. There is no formal on-call rotation yet, but one may be introduced.
Key Responsibilities:
1. Threat Modelling & Secure Design
• Agentic Threat Modelling: Threat model agents, tools, MCP servers, and multi-agent workflows
using the OWASP Top 10 for LLM Applications, OWASP Agentic AI threats, and MITRE ATLAS, and run
a lightweight pre-launch review gate.
• Secure-by-Default Reviews: Review agentic code and designs, publish secure defaults, and make
risk trade-offs explicit and owned.
• Security Knowledge Sharing: Teach secure agent practices within the team and to other Brahma
teams through guides, threat-model walkthroughs, demos and office hours.
2. Identity, Isolation & Guardrails
• Agent & Tool Identity: Design authentication and authorisation for agents and tools with OAuth
2.0/OIDC, token exchange, and scoped, short-lived credentials, with per-tool least privilege,
fail-closed MCP authorisation, and secrets kept out of agent runtimes.
• Sandboxed Execution: Harden the containers and sandboxes where coding agents and tool calls
run, with filesystem isolation, egress control, and human approval for irreversible actions.
• Guardrails & Policy Enforcement: Build gateway defences against direct and indirect prompt
injection, tool abuse, excessive agency, and data exfiltration: input and output filtering, PII/DLP , and
policy-as-code, tuned so they do not stall developers.
3. Adversarial Testing & Supply Chain
• AI Red-Teaming: Build an automated adversarial test suite (injection, tool misuse, exfiltration, goal
drift) that runs in CI and on a schedule, so we can show controls work, not only that they exist.
• Supply-Chain Security: Govern which MCP servers, skills, plugins, models, and dependencies we
adopt, through review, allow-listing, signing, SBOMs, and scanning.
4. Detection, Response & Compliance
• Audit Logging & Detection: Make every model, tool, and agent call traceable to a person and an
agent, and feed guardrail events and anomalies into security monitoring and alerting.
• Production Security Ownership: Own the security controls once they are live: monitor their
effectiveness, tune guardrails from production data, and keep them patched and current as models,
tools and standards change.
• Incident Response & Compliance: Own the playbook for agent-related incidents and lead the
technical response. Map controls to ISO 27001, ISO/IEC 42001, SOC 2, GDPR, and TPN, and keep
evidence audit-ready.
Job Requirements / Must Haves
• Security Engineering Background: 5+ years in security engineering with a strong application or
product security component, and fluent Python.
• Build, Not Only Audit: Track record of shipping security tooling, controls, and automated tests as
production code.
• LLM & Agent Security: Hands-on experience securing LLM applications or agents against prompt
injection and unsafe tool use.
• Identity & Authorisation: Deep knowledge of OAuth 2.0, OIDC, token exchange, workload identity,
and least-privilege design.
• Threat Modelling: Experience leading structured threat modelling and turning findings into
prioritised engineering work.
• Secure SDLC & DevSecOps: Experience embedding security scanning and checks into CI/CD, and
securing containerised workloads.
• Risk Communication: Ability to explain risk and trade-offs clearly to engineers and leadership, and
to document decisions.
• Knowledge Sharing: Track record of teaching and documenting security practices for colleagues and
other teams.
Nice to Have:
• AI Red-Teaming Tools: Experience with garak, PyRIT, promptfoo, or similar.
• Policy Engines: Practical use of OPA/Rego, Cedar, or similar.
• Sandboxing Technology: Familiarity with gVisor, Firecracker, seccomp, or Landlock.
• Agent Infrastructure: Experience building or securing MCP servers, LLM gateways, or guardrail
services.
• GCP: Working knowledge of IAM, Workload Identity, Secret Manager, and Cloud Logging.
• AI Governance & Media Security: Exposure to ISO/IEC 42001, NIST AI RMF, or MPA/TPN content
security.
• Certifications: OSCP , GIAC, CSSLP , or equivalent.
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