AI Swarm & Multi-Agent Orchestration Architect
Architect scalable multi-agent consensus networks, decentralized task delegation, conflict resolution algorithms, and collaborative swarm problem-solving.
Role Overview & Operational Scope
Individual models have inherent context and competence limits; swarms of specialized agents break through these barriers. As our AI Swarm Architect, you will design the organizational hierarchy, voting protocols, and verification gates that allow heterogeneous agents to work together seamlessly without cascading errors.
Key Responsibilities & Production Deliverables
- Architect dynamic task-allocation graphs that autonomously break down monolithic enterprise objectives into discrete sub-agent tasks.
- Implement Byzantine-resilient consensus and peer-review protocols where agents cross-validate each other's code and findings.
- Design automated conflict-resolution mechanisms for handling contradictory outputs from distinct specialized agents.
- Optimize multi-agent token economies and execution budgets to maximize business throughput while controlling compute expenditure.
- Build real-time swarm visualizers and intervention dashboards for human-in-the-loop oversight.
Mandatory Foundational Knowledge
- Swarm robotics, decentralized optimization, game theory, and multi-agent reinforcement learning (MARL).
- State machine design, Directed Acyclic Graph (DAG) execution engines, and topological sorting.
- Distributed systems fault tolerance, dead-lock detection, and leader election protocols.
Mandatory Practical Skills & Architecture
- Advanced Python development with experience in multi-agent frameworks (LangGraph, AutoGen, CrewAI, or custom engines).
- Strong backend integration experience with asynchronous queuing and state persistence.
- Proficiency in building automated telemetry and trace visualizers.
Problem Solving, Execution Rigor & Curiosity
- Fascinated by emergent behaviors in decentralized biological systems (ant colonies, market economies).
- Disciplined engineer who prioritizes deterministic convergence over chaotic agent interactions.
- Relentless optimizer of system efficiency and multi-tenant scalability.
5-Day Live Technical Evaluation Milestone
5-Day Live Practical Milestone: Architect a 5-node collaborative agent swarm where specialized agents autonomously negotiate, review, and merge code pull requests with zero human intervention (strictly 5 working days).
Institutional Hiring Protocol: Candidates who pass initial resume screening are invited to a live, practical evaluation milestone spanning strictly not more than 5 working days. Verifiable completion and code audit by your assigned senior engineering mentor is the sole prerequisite for official corporate offer letter issuance.
Compensation, Total Rewards & Advancement
- Competitive senior salary (₹13,00,000–₹23,00,000) with project delivery bonuses.
- High-visibility position building products used by multinational enterprise clients.
- Full remote work support with flexible hours.
- Continuous access to frontier models and high-throughput API tiers.
Dedicated Inquiries Inbox for This Role
Have questions regarding architecture scope or wish to share private research repos directly? Messages sent to this address route straight to the engineering leads reviewing this opening.
ai-swarm-multi-agent-architect-careers@cehpoint.co.in
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