Senior AI Engineer (Agentic Systems & Inference) - Onsite - Riyadh at COGNNA

Riyadh, Riyadh Region, Saudi Arabia -

Full Time

Start Date

Immediate

Expiry Date

28 Apr, 26

Salary

0.0

Posted On

28 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Backend Systems, Multi-Agent Systems, Cognitive Optimization, Model Fine-Tuning, MLOps, Distributed Inference, Cloud AI, Python, Go, C++, Kubernetes, Quantization, Security Models, Observability, Agentic Systems

Industry

Computer and Network Security

Description

As a Senior AI Engineer, you will be the primary architect of Cognna’s autonomous agent reasoning engine and the high-scale inference infrastructure that powers it. You are responsible for building production-grade reasoning systems that proactively plan, use tools, and collaborate. You will own the full lifecycle of our specialized security models, from domain-specific fine-tuning to architecting distributed, high-throughput inference services that serve as Security-core intelligence in our platform. Key Responsibilities 1. Agentic Architecture & Multi-Agent Coordination Autonomous Orchestration: Design stateful, multi-agent systems using frameworks like Google ADK. Protocol-First Integration: Architect and scale MCP servers and A2A interfaces, ensuring a decoupled and extensible agent ecosystem. Cognitive Optimization: Develop lean, high-reasoning microservices for deep reasoning, optimizing context token usage to maintain high planning accuracy with minimal latency. 2. Model Adaptation & Performance Engineering Specialized Fine-Tuning: Lead the architectural strategy for fine-tuning open-source and proprietary models on massive cybersecurity-specific telemetry. Advanced Training Regimes: Implement Quantization-Aware Training (QAT) and manage Adapter-based architectures to enable the dynamic loading of task-specific specialists without the overhead of full-model swaps. Evaluation Frameworks: Engineer rigorous, automated evaluation harnesses (including Human annotations and AI-judge patterns) to measure agent groundedness and resilience against the Security Engineer’s adversarial attack trees. 3. Production Inference & MLOps at Scale Distributed Inference Systems: Architect and maintain high-concurrency inference services using engines like vLLM, TGI, or TensorRT-LLM. Infrastructure Orchestration: Own the GPU/TPU resource management strategy. Observability & Debugging: Implement deep-trace observability for non-deterministic agentic workflows, providing the visibility needed to debug complex multi-step reasoning failures in production. 4. Advanced RAG & Semantic Intelligence Hybrid Retrieval Architectures: Design and optimize RAG pipelines involving graph-like data structures, agent-based knowledge retrieval and semantic searches. Memory Management: Architect episodic and persistent memory systems for agents, allowing for long-running security investigations that persist context across sessions. Experience: 5+ years in AI/ML Engineering or Backend Systems. Must have contributed to large-scale AI/ML inference service in production. Education: B.S/M.S. in Compuper Science, Engineering, AI, or related fields. Inference Orchestration: KV-cache management, quantization formats like AWQ/FP8, and distributed serving across multi-node GPU clusters). Agentic Development: Expert in building autonomous systems using Google ADK/Langgraph/Langchain and experienced with AI Observervability frameworks like LangSmith or Langfuse. Hands-on experience building AI applications with MCP and A2A protocols. Cloud AI Native: Proficiency in Google Cloud (Vertex AI), including custom training pipelines, high-performance prediction endpoints, and the broader MLOps suite. Programming: Python and experience with high-performance backends (Go/C++) for inference optimization. You are comfortable working in a Kubernetes-native environment. CI/CD: You are comfortable working in a Kubernetes-native environment. 💰 Competitive Package – Salary + equity options + performance incentives 🧘 Onsite Experience – Work from our office in Riyadh, KSA 🤝 Team of Experts – Work with designers, engineers, and security pros solving real-world problems 🚀 Growth-Focused – Your ideas ship, your voice counts, your growth matters 🌍 Global Impact – Build products that protect critical systems and data

Responsibilities

The Senior AI Engineer will architect Cognna’s autonomous agent reasoning engine and high-scale inference infrastructure. Responsibilities include designing multi-agent systems, fine-tuning models for cybersecurity, and managing production inference services.