Security Engineer

AI Security Engineer

Role Summary

● We are hiring an AI Engineer who will build agentic systems and AI-driven automation
for our security and infrastructure functions.
● The ideal candidate is AI-native first — fluent in LLMs, agent frameworks, and
prompt/context engineering — with working knowledge of security and a strong
grasp of infra/deployment.
● This is not a traditional security engineering role. We want someone who thinks in terms
of agents, tools, and orchestration, and who can ship AI systems that operate against
real production infrastructure.
● Reports into Security/Platform leadership; collaborates with SecOps, CloudSec, AppSec,
and SRE teams.

What You'll Build
● Agentic security workflows — multi-agent systems (planner-executor,
orchestrator-subagent) for IR triage, threat hunting, alert correlation, and compliance
evidence collection.
● MCP servers and clients that wrap internal tools (SentinelOne, Zscaler, AWS APIs,
Active Directory, Jamf, Semgrep, etc.) so agents can act on production systems.
● AI-driven infra automation — agents that deploy, configure, and remediate Kubernetes
workloads, IAM policies, network rules, and cloud resources.
● LLM-powered detection and response pipelines — log summarisation, anomaly
explanation, runbook execution, and automated containment with human-in-the-loop
guardrails.
● Evals, guardrails, and safety layers for production AI systems handling sensitive data.
● Internal AI platform — gateways, model routing, prompt registries, and observability for
LLM use across the org.

Must-Have: AI Engineering
● Hands-on experience building production systems with Claude (Anthropic API),
OpenAI, or equivalent frontier LLMs — not just chatbot demos.
● Strong prompt engineering and context engineering — understands tool-use loops,
structured outputs, evals, and failure modes.
● Built at least one agentic system end-to-end — planner-executor, ReAct,
orchestrator-subagent, or similar.
● Experience with MCP (Model Context Protocol) — has built MCP servers/clients or
equivalent tool-wrapping abstractions.
● Comfort with agent frameworks — Claude Agent SDK, LangGraph, AutoGen, CrewAI,
or custom orchestration.
● Working knowledge of local inference — Ollama, LM Studio, vLLM, llama.cpp — and
proxy layers like LiteLLM.
● Familiarity with fine-tuning, RAG, and embeddings — knows when to reach for each.
● Has shipped at least one AI system that took real actions on real systems (not
read-only analysis).

Must-Have: Infra & Deployment
● Strong Kubernetes chops — has deployed and operated workloads on EKS/GKE/AKS,
written Helm charts or Kustomize, and debugged pod/networking/RBAC issues.
● AWS or GCP depth — IAM, VPC, networking, secrets, observability.
● Infrastructure as Code — Terraform, Pulumi, or CDK.
● CI/CD — GitHub Actions, ArgoCD, or similar; understands deployment patterns
(blue-green, canary).
● Comfortable making agents drive infra changes — knows the diff between "agent
suggests a Terraform plan" and "agent applies it" and how to gate the latter safely.
● Container security basics — image scanning, Pod Security Standards, admission
controllers.

Nice-to-Have: Security Knowledge (Add-on)
● Familiarity with at least one of: SIEM/XDR (SentinelOne, Splunk), SAST/DAST
(Semgrep, Burp), CSPM (Wiz, Prowler), or DLP/SSE (Zscaler).
● Awareness of OWASP Top 10 for LLMs, prompt injection, jailbreaks, and data exfil via
LLMs.
● Conceptual understanding of compliance regimes — PCI DSS, ISO 27001, SOC 2, RBI,
DPDP — enough to know what "evidence" means.
● Threat modelling fundamentals (STRIDE) and MITRE ATT&CK literacy.
● Note: We are not looking for a CISSP profile. Security knowledge is an add-on; AI
engineering and infra are the primary bar.
Mindset
● Builder, not just a researcher — ships systems, not just notebooks.
● Pragmatic about AI — knows what LLMs are bad at and designs around it
(deterministic fallbacks, validators, human-in-the-loop).
● Safety-aware — thinks about prompt injection, tool abuse, and blast radius before an
agent gets sudo.
● Comfortable with ambiguity — this space changes monthly; you should enjoy that.

Location - Bangalore
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