Forward Deployed AI Engineer
Summary
Deploys, integrates, and optimizes enterprise GenAI platforms (Tangram.ai, NVIDIA NIMs, LLMs, DataRobot) inside secure, on-premise and air-gapped banking environments in Saudi Arabia. Day-to-day is hands-on with Red Hat OpenShift, Kubernetes, NVIDIA GPU Operator, Helm/Kustomize, and ArgoCD/GitOps pipelines, working directly with client IT, security, and infrastructure teams.
Who are we?
Crayon Data is a leading provider of AI-led revenue acceleration solutions, headquartered in Singapore with a presence in India and the UAE. Founded in 2012, our mission has always been to simplify the world’s choices.
Today, we’ve evolved into Tangram.ai — a modular, GenAI-powered platform built for the enterprise. Tangram lets organizations assemble intelligent agents, solutions, and models like building blocks to create, scale, and adapt AI-powered capabilities with speed, security, and precision. It’s not just a platform,it’s the operating layer for GenAI in the enterprise.
Role Overview
We are looking for a Forward Deployed AI Engineer to deploy, integrate, optimize, and operationalize enterprise Generative AI platforms within secure, on-premise and air-gapped banking environments.
You will work closely with client IT, infrastructure, security, engineering, and AI teams to turn AI platform architectures into reliable, production-ready deployments.
What You'll Do
- Deploy and configure NVIDIA NIMs, LLMs, DataRobot, Graph Databases, and related AI platforms.
- Install and manage AI workloads on Red Hat OpenShift and Kubernetes environments.
- Package and deploy container images, dependencies, and LLM model weights in air-gapped environments.
- Configure and optimize NVIDIA GPU Operator, GPU time-slicing and MIG for AI workloads.
- Optimize LLM inference performance, including TTFT, throughput, latency and GPU utilization.
- Build and manage CI/CD and GitOps pipelines using tools such as ArgoCD and OpenShift Pipelines.
- Develop and maintain Helm charts, Kustomize manifests and Kubernetes configurations.
- Troubleshoot deployment, infrastructure, networking and performance issues in secure client environments.
- Work directly with client IT, Security and Infrastructure teams to resolve technical blockers and ensure successful deployments.
What We're Looking For
- 4+ years of experience in Software Engineering, DevOps, Platform Engineering or a related field.
- 2+ years of hands-on experience in MLOps / LLMOps.
- Strong experience with Red Hat OpenShift and Kubernetes.
- Hands-on experience with NVIDIA GPUs and NVIDIA GPU Operator.
- Experience deploying LLMs, NVIDIA NIM, Triton or enterprise AI platforms.
- Strong understanding of containerization, Docker/OCI images and Kubernetes workloads.
- Experience with Helm, Kustomize, Kubernetes Operators and GitOps.
- Experience with ArgoCD, OpenShift Pipelines or similar CI/CD tools.
- Understanding of air-gapped / disconnected environments and offline software deployment.
- Good understanding of enterprise authentication and security frameworks such as Active Directory, LDAP, Kerberos and OAuth.
- Experience with secure secrets management using HashiCorp Vault, OpenShift Secrets or similar technologies.
- Strong troubleshooting, communication and client-facing skills.
Brownie Points
- Experience deploying AI platforms in Banking / BFSI or highly regulated environments.
- Experience working in air-gapped or disconnected data centers.
- CKA / CKAD certification.
- Experience with NVIDIA NIM, Triton Inference Server or DataRobot.
- Experience with Graph Databases such as Neo4j or ArangoDB.
- Experience with GPU performance tuning, MIG and GPU time-slicing.
- Experience with large-scale LLM inference and RAG deployments.