Research Engineer – Multi-Agent Systems & A2A Intelligence

Randstad Türkiye; Fatih; On-site; TRY 120,000 - 230,000; Full time

Job summary

Randstad Türkiye is seeking Research Engineers in Computer Science or Artificial Intelligence to tackle distributed agent coordination, negotiation protocols, and semantic alignment for next-gen autonomous networks.

You will conduct cutting-edge applied research, publish in top AI and networking venues, and collaborate with global operators and academic partners.

Qualifications

• PhD or MSc with strong research record in MAS, AI, or related areas.
• Proven publication track record in top venues.
• Excellent English communication, written and spoken.
• Strong programming skills in Python and DL frameworks (PyTorch, LangGraph, AutoGen).

Responsibilities

• Conduct fundamental and applied research at the intersection of Multi-Agent Systems, Foundation Models, and Autonomous Systems.
• Design novel algorithms, protocols and prototypes for real-world and simulated networks.
• Publish findings in top AI and networking venues (e.g., NeurIPS, ICML, SIGCOMM).
• Collaborate with operators, industrial partners, and academic colleagues on patents and standards.

Skills

Research experience

Python programming

English communication

Education

PhD in related area

MSc with 3+ years research

Tools

PyTorch

Distributed AI frameworks

LangGraph

AutoGen

Job description

Türkiye R&D Center is pioneering the next frontier of autonomous network intelligence through OpenAN (Open Autonomous Networks) and Agent-to-Agent (A2A) collaboration architectures for 5.5G and future 6G systems.

We are seeking Research Engineers in Computer Science or Artificial Intelligence to join our research team. In this role, you will tackle fundamental challenges in distributed agent coordination, collaborative negotiation protocols, semantic intent alignment, and safe agentic workflows. You will conduct cutting-edge applied research with direct impact on carrier-grade networks operating at global scale.

Key Research Focus Areas

1- Agent-to-Agent (A2A) Coordination & Negotiation Protocols

• Distributed multi-agent architectures for autonomous cross-domain network orchestration.
• Negotiation protocols, dynamic consensus mechanisms, and conflict resolution in heterogeneous multi-agent systems.
• Deadlock detection, prevention, and cycle-breaking in iterative multi-agent communications.

2- Intent Understanding, Knowledge Graphs & Semantic Alignment

• Natural language intent parsing and bidirectional translation between business objectives and technical network configurations.
• Domain-specific Knowledge Graph (KG) construction, ontology design, and schema alignment across OSS and RAN domains.
• Multi-turn dialogue management and persistent memory architectures for autonomous agents.
• Hallucination detection and mitigation in LLM-based autonomous decision-making loops.
• Trust models, formal verification, and policy guardrails for agent-to-agent interactions in critical infrastructure.

Key Responsibilities

• Conduct fundamental and applied research at the intersection of Multi-Agent Systems, Foundation Models, and Autonomous Systems.
• Design novel algorithms, protocols, and architectural prototypes validated on real-world and simulated network environments.
• Publish research findings in top-tier AI and networking venues (e.g., NeurIPS, ICML, ICLR, AAAI, AAMAS, SIGCOMM, INFOCOM).
• File high-value international patents and contribute novel proposals to global standardization initiatives (e.g., 3GPP, O-RAN, ITU-T).
• Collaborate with global Telecom Operators, Huawei HQ researchers, and local academic partners at top Turkish universities.

Qualifications Required:

• PhD with strong publication in related area / MSc Degree with 3+ years research experience in academics/industry
• Demonstrated research track record in at least two of the following areas:
• Multi-Agent Systems (MAS), Game Theory, or Distributed AI
• Large Language Model (LLM) Agents, Tool Use, and Agentic Workflows
• Knowledge Graphs, Ontologies, or Semantic Web
• Natural Language Processing (NLP) / Information Extraction
• Formal Methods, Deadlock Prevention, or Consensus Protocols
• Solid publication record in reputable conferences or journals.
• Strong programming skills in Python and deep learning/agent frameworks (e.g., PyTorch, LangGraph, AutoGen, or custom distributed agent platforms).
• Excellent English communication skills (written and verbal).

Preferred:

• Prior exposure to telecommunications concepts, network management (OSS/RAN), or 3GPP service architecture (helpful, but domain background will be provided).
• Experience with open-source foundation models (fine-tuning, RLHF, alignment, quantization).
• Track record of filing patents or contributing to open-source systems.