What you will be doing:
Design, build, and maintain reusable AI capabilities – including models, tools, APIs, and platforms that power both internal and customer-facing solutions.
Develop and maintain our internal MCP server that easily and securely exposes Forters vast data stores to AI agents.
Create and implement robust evaluation frameworks and AI guardrails to safeguard Forters value and ensure model reliability.
Establish deep expertise and sustainable AI engineering practices.
Promote AI readiness and track adoption across the company to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Take full ownership of projects: from gathering requirements from non-technical internal users to development, deployment, and operation.
Act as a consultant and advocate for AI engineering, helping other teams leverage the platforms and tools you build.
Partner with teams across us to accelerate AI adoption and productization efforts.
5+ years of strong backend and server-side development experience, building complex, highly scalable systems.
Proven experience with at least one general-purpose language (preferably Python, but not a must).
Strong product management skills, with the ability to gather and refine requirements from non-technical internal users.
A strong sense of ownership, with some DevOps experience and a willingness to develop, deploy, and run projects end-to-end.
Solid understanding of GenAI, LLMs and foundation models.
Strong familiarity with AI coding tools like Claude Code, Github Copilot, Cursor, or similar.
Hands-on experience with building AI-driven workflows, agentic frameworks, evals, RAGs, MCPs, skills, etc.
Experience working with public clouds (AWS / GCP / Azure).
Fluent in written and spoken English.
