Forward Deployed Engineer Generative AI / LLM Deployment
GenAI | LangChain | RAG | AWS | Kubernetes | Client-Facing
Were looking for a Forward Deployed Engineer to drive the implementation and rollout of enterprise-grade Generative AI and LLM solutions within production environments.
This is a hands-on, customer-facing position focused on architecting and deploying RAG pipelines, agent-based systems, and fine-tuned LLM applications using frameworks such as LangChain and LangGraph. You will work closely with client teams, take full ownership of technical delivery from proof of concept through to production, and deliver measurable KPI-driven outcomes.
Key Responsibilities Architect and implement GenAI / LLM solutions (RAG, agentic workflows, fine-tuning)
Lead cloud-based production deployments across AWS, Azure, or GCP
Develop scalable backend services in Python (JavaScript is advantageous)
Manage and provision infrastructure using Kubernetes, Docker, and Terraform
Own end-to-end technical delivery across multiple enterprise engagements
Perform debugging, optimisation, and root cause analysis
Clearly communicate complex AI concepts to both technical and non-technical stakeholders
Requirements Proven experience building and deploying LLM / Generative AI applications
Strong hands-on expertise with LangChain, RAG architectures, and multi-agent systems
Experience deploying ML solutions in cloud environments (AWS, Azure, or GCP)
Familiarity with DevOps practices and tooling: Kubernetes, CI/CD, GitHub, GitOps
Prior experience in client-facing technical delivery roles
Background in Machine Learning, Data Science, or AI Engineering
This opportunity is ideal for a Senior Machine Learning Engineer, Applied AI Engineer, AI Solutions Engineer, or LLM Engineer who thrives on client engagement, rapid experimentation, and taking ownership of delivery in fast-paced environments.
Apply now to help shape the next generation of enterprise AI and agentic system deployments.
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