AI Architect

A well-funded startup that has raised $16M is developing an intelligent chatbot designed to significantly reduce the workload of DevOps teams. The company has strong business partners and customers worldwide.

This is a high-impact role, reporting directly to the CTO, leading the entire AI infrastructure of the company a key position with substantial influence on the company's growth and technological direction.

Join a young and dynamic startup that requires a high level of commitment and hands-on effort, but offers excellent compensation and benefits in return.

The team includes around 20 employees, 15 of whom are based in Israel. The company is located in the Bursa district and operates in a hybrid model (two days from home).

About the role

• Craft cloud-native, micro-service architectures for training, fine-tuning and real-time inference (AWS/GCP/Azure, Kubernetes, JetStream).
• Define SLOs for p95 agent latency, model success rate, and telemetry coverage; instrument with OTEL, Prometheus and custom reward models.
• Drive our continuous-learning loop: reward modelling, ContextGraph enrichment, auto-tuning MoE routers.
• Embed least-privilege IAM and OPA/ABAC policy checks into every stage of the model lifecycle.
• Collaborate with product managers to translate customer pain into roadmap items and with design partners to validate solutions in production.
• Mentor a cross-functional squad of backend engineers, ML engineers and data scientists.

Requirements-

• 8 years in software engineering, with 3+ years architecting large-scale backend systems
• 4 years designing, deploying and monitoring AI/ML systems in production.
• Deep expertise in at least one of: large-language-model serving, MoE routing, RLHF, vector search, streaming inference.
• Hands-on fluency with Kubernetes, Docker, CI/CD, IaC (Terraform/Helm) and distributed data technologies (Kafka, Spark, Arrow).
• Proven MLOps track record (MLflow, Kubeflow, SageMaker, or similar) and a security-first mindset.
• Ability to turn ambiguous business goals into a crisp, scalable architecture — and to communicate that vision to both executives and engineers.