Senior Applied AI Engineer

About the role

We are looking for a Senior Applied AI Engineer to design, build and ship production‑grade AI systems for our clients. The role combines hands‑on development, infrastructure deployment and client‑facing explanation of system behaviour.

Key responsibilities

• Design and implement applied AI solutions on Claude and AWS Bedrock AgentCore, including RAG pipelines, agentic workflows and multi‑tool orchestration via MCP.
• Own end‑to‑end delivery of AI components: architecture, coding, evaluation, monitoring and post‑launch support.
• Integrate Claude‑based agents with client tools such as Notion, Linear, HubSpot, Google Workspace and AWS through MCP servers.
• Translate ambiguous client problems into scoped technical builds with clear success metrics.
• Document architecture and decisions in client Notion workspaces.
• Collaborate with Pre‑Sales Engineers to validate technical feasibility during scoping calls.
• Select and tune models, retrieval strategies and Knowledge Base configurations per use case.
• Build and maintain evaluation suites to detect quality drift.
• Design agentic control flows, guardrails and fallback mechanisms.
• Instrument production systems with logging, tracing and cost/latency dashboards.
• Write modular infrastructure‑as‑code (Terraform) for AI workloads on AWS.
• Conduct architecture reviews of peers’ AI builds and flag potential failure modes.

Required profile

• Master’s degree in Computer Science or equivalent.
• Proven experience building and shipping production ML/AI systems.
• Fluent in English and Arabic.

Required skills

• Strong Python engineering.
• Hands‑on experience with AWS, Terraform and AWS Bedrock (AgentCore, Knowledge Bases).
• Practical knowledge of LLM application patterns: Retrieval‑Augmented Generation, agentic tool‑use via MCP, prompt engineering and evaluation design.
• Experience integrating AI agents with business tools (Notion, Linear, HubSpot, Google Workspace).