Enterprise AI Architect - Agentic Systems & Pre-Sales

Prometa AI; Fatih; On-site; TRY 350,000 - 700,000; Full time

Job summary

Prometa AI is seeking an AI Architect to lead the design and deployment of scalable, production-ready AI infrastructures. You will architect multi-agent, LLM-driven systems and drive customer engagements, proof-of-concept sessions, and technical workshops.

Responsibilities include enterprise integration across on-premise and cloud platforms, building robust data pipelines, ensuring GDPR/KVKK compliance, and overseeing containerized deployments with Kubernetes/OpenShift.

Qualifications

• Bachelor’s or Master’s degree in CS/AI or related field.
• 10+ years designing enterprise-scale AI/ML solutions.
• 3+ years in agentic or presales AI architecture.
• Ability to explain complex AI concepts to executives.
• Experience with multi-agent orchestration and real-time AI systems.

Responsibilities

• Architect Agentic AI Systems: design multi-agent architectures (LLM-driven, RAG-enabled, planning/reasoning).
• Conduct on-site and virtual meetings to identify AI opportunities and demonstrate solutions.
• Design data ingestion pipelines and retrieval systems for enterprise data.
• Ensure AI systems comply with GDPR, KVKK, MASAK and other frameworks.
• Oversee containerized, GPU-optimized deployments (Kubernetes/OpenShift).
• Mentor AI/ML engineers and present to C-level stakeholders.

Skills

Agentic AI design

LLM engineering

Presales & storytelling

C-level communication

Multi-agent orchestration

Data integration

Security & compliance

Research awareness

Education

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field

Tools

LangGraph

Semantic Kernel

CrewAI

AutoGen

Kubeflow

MLflow

Argo

Tekton

Kubernetes

OpenShift

REST

gRPC

Kafka

RabbitMQ

MuleSoft

Job description

Prometa AI is seeking an AI Architect to lead the design and deployment of scalable, production-ready AI infrastructures. You will architect multi-agent, LLM-driven systems and drive customer engagements, proof-of-concept sessions, and technical workshops.

Responsibilities include enterprise integration across on-premise and cloud platforms, building robust data pipelines, ensuring GDPR/KVKK compliance, and overseeing containerized deployments with Kubernetes/OpenShift.