Forward Deployed AI Engineer

About the role

Keyrus is seeking a Forward Deployed AI Engineer to work directly with clients on their most urgent AI challenges. In this role you will translate business intent into operational AI solutions within weeks, combining hands‑on engineering, architectural judgment and business insight.

Key responsibilities

• Co‑create AI solutions with business and technical stakeholders through workshops, rapid iterations and hands‑on delivery.
• Identify, qualify and secure the data required for each use case, collaborating closely with Data Engineers.
• Translate use cases into production‑ready Generative AI and agentic AI solutions, including Retrieval‑Augmented Generation (RAG) architectures, intelligent assistants and AI‑enabled workflows.
• Prototype, test, deploy, monitor and continuously improve solutions in real client environments.
• Work with cross‑functional teams (Data Engineers, Software Engineers, Foundations Architects, Governance experts, Business Value Advisors, Service Delivery Managers) to ensure sustainable outcomes.
• Balance speed, quality, cost, security and maintainability while making clear technical trade‑offs.
• Define success criteria (adoption, performance, reliability, risk, cost, measurable business value) from the outset.
• Document, govern and hand over solutions so clients can operate them confidently.
• Convert successful deliveries into reusable patterns, accelerators and building blocks for future engagements.

Required profile

• Hands‑on engineer who thinks like an architect and builds end‑to‑end AI solutions.
• Strong ability to work closely with clients, understand ambiguous problems and drive them to measurable results.
• Experience delivering AI projects at scale, preferably in a consulting or client‑facing environment.
• Excellent judgment to balance technical trade‑offs and business value.

Required skills

• Generative AI (GenAI) development.
• Agentic AI and intelligent assistant design.
• Retrieval‑Augmented Generation (RAG) architectures.
• AI‑enabled workflow implementation.
• Data acquisition and preparation for AI use cases.