Salary: INR 2500000-3500000 / year (based on experience)
Expected Notice Period: 15 Days
Shift: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type: Remote
Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: CognitivTrust Inc)
(*Note: This is a requirement for one of Uplers client - CognitivTrust Inc)
What do you need for this opportunity?
Must have skills required:
AppSec, DevSecOps, MCP, Vulnerability management, Agentic AI, Agentic AI Workflows in production, crewAI, CyberSecurity, LangChain
CognitivTrust Inc is Looking for:
About CognitivTrust CognitivTrust is building the security infrastructure layer for the Agentic SDLC era. As AI fundamentally transforms how software is written, were creating the platform that makes it safe to ship at AI speed. We sit between AI coding tools (Cursor, Claude Code, Copilot) and enterprise security stacks—providing real-time security context where code is born. The Role Were looking for an AI Engineer to design and build fully autonomous agents that power our security platform. Youll create systems that reason, act, and adapt—agents that analyze code, identify vulnerabilities, orchestrate remediation, and integrate with complex enterprise environments without human intervention. This isnt prompt engineering. This is building production-grade agentic systems that operate reliably at scale. What Youll Do
Design and implement autonomous agents for security analysis, threat modeling, and remediation
Build multi-agent orchestration systems with configurable autonomy levels
Experience building and deploying production systems at scale
Deep understanding of agent architectures—ReAct, tool use, planning, reflection Enterprise Agent Experience
Built and deployed autonomous agents in enterprise production environments—not prototypes, not demos
Implemented end-to-end agentic workflows that handle real business processes with minimal human oversight
Designed agents that integrate with enterprise systems (APIs, databases, SaaS platforms) and handle authentication, rate limits, and failure recovery gracefully
Experience with agent observability—logging, tracing, debugging autonomous systems in production
Built human-in-the-loop checkpoints and escalation paths for high-stakes agent decisions Agentic Systems Design
Hands-on experience designing multi-agent systems with clear task decomposition and coordination
Implemented configurable autonomy levels—knowing when agents should act vs. ask
Built evaluation and testing frameworks for non-deterministic agent behavior
Experience with agent memory systems—short-term context, long-term knowledge, retrieval
Familiarity with agent frameworks (LangGraph, CrewAI, AutoGen) or built custom orchestration layers Bonus
Experience with MCP or similar agent-tool protocols
Background in enterprise software or B2B SaaS What Sets You Apart
Youve built agents that run autonomously in production for weeks, not hours
You think in systems—reliability, observability, failure modes, edge cases
Youre obsessed with evaluation and know that vibes-based testing doesnt scale
You understand that enterprise means auditability, compliance, and zero surprises
You ship fast and iterate based on real-world feedback
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