GenAI | LangChain | RAG | AWS | Kubernetes | Customer-Facing

We are hiring a Forward Deployed Engineer to lead the deployment of production-grade Generative AI and LLM solutions into enterprise environments.

This is a hands-on, customer-facing role focused on building and deploying RAG pipelines, multi-agent systems and fine-tuned LLM applications using tools such as LangChain and LangGraph. You will embed with client teams, own technical delivery from prototype to production, and demonstrate measurable KPI impact.

Key Responsibilities

* Design and deploy GenAI / LLM applications (RAG, agentic AI, fine-tuning)

* Lead production deployment on AWS, Azure or GCP

* Build scalable backend systems in Python (JavaScript a plus)

* Manage infrastructure using Kubernetes, Docker, Terraform

* Own end-to-end technical delivery across multiple client deployments

* Conduct debugging, optimisation and root cause analysis

* Communicate complex AI concepts to technical and non-technical stakeholders

Requirements

* Strong experience building and deploying LLM / Generative AI solutions

* Hands-on with LangChain, RAG, multi-agent systems

* Cloud ML deployment experience (AWS, Azure or GCP)

* DevOps tooling: Kubernetes, CI/CD, GitHub, GitOps

* Customer-facing technical delivery experience

* Background in Machine Learning, Data Science or AI Engineering

This role suits a Senior Machine Learning Engineer, Applied AI Engineer, AI Solutions Engineer or LLM Engineer who enjoys client impact, rapid prototyping and owning delivery in fast-moving environments.

Apply now to work at the forefront of enterprise AI deployment and agentic systems