Forward Deployed AI Engineer

Forward Deployed AI Engineer – Transforming Enterprise AI Deployments in High-Security Banking Environments

At Tangram.ai, we are pioneering the future of enterprise-grade Generative AI with our modular, GenAI-powered platform. Our mission is to empower organizations to build, scale, and adapt AI-driven solutions with unmatched speed, security, and precision. As a Forward Deployed AI Engineer, you will play a critical role in deploying, optimizing, and operationalizing cutting-edge AI platforms within the most secure, air-gapped, and high-stakes banking environments. This is not just a technical role—it’s an opportunity to architect and deliver AI solutions that redefine enterprise capabilities in one of the most regulated industries.

In this forward-deployed capacity, you will collaborate directly with client teams—including IT, infrastructure, security, and AI specialists—to translate complex AI architectures into seamless, production-ready deployments. Your expertise will bridge the gap between innovation and execution, ensuring that Tangram.ai’s GenAI platform is deployed with the highest standards of performance, reliability, and security.

Your Impact: Driving AI Excellence in Banking

As a Forward Deployed AI Engineer, your responsibilities will include:

• Deploying and Optimizing AI Platforms: Expertly configure and deploy NVIDIA NIMs, Large Language Models (LLMs), and enterprise AI platforms like DataRobot and Graph Databases in secure, air-gapped environments. Leverage your knowledge of NVIDIA GPUs, GPU Operator, and advanced techniques like Multi-Instance GPU (MIG) to maximize performance and efficiency.
• Mastering Kubernetes and Cloud-Native Technologies: Install, manage, and optimize AI workloads on Red Hat OpenShift and Kubernetes environments. Package and deploy containerized AI models, dependencies, and LLM weights while ensuring compatibility with disconnected or air-gapped systems.
• Building Robust CI/CD and GitOps Pipelines: Develop and maintain automated pipelines using tools like ArgoCD and OpenShift Pipelines to streamline deployments, reduce manual errors, and accelerate time-to-market for AI solutions.
• Troubleshooting and Resolving Technical Challenges: Diagnose and resolve complex deployment, infrastructure, networking, and performance issues in highly regulated environments. Work closely with client teams to overcome technical blockers and ensure seamless AI integration.
• Advancing LLM Inference and Performance: Optimize LLM inference performance, focusing on key metrics such as Time to First Token (TTFT), throughput, latency, and GPU utilization to deliver high-performance AI solutions.
• Ensuring Security and Compliance: Implement enterprise-grade authentication frameworks (e.g., Active Directory, LDAP, Kerberos, OAuth) and secure secrets management (e.g., HashiCorp Vault) to safeguard AI deployments in compliance with banking regulations.

Why This Role Matters

You are more than an engineer—you are a trusted partner in deploying AI at the forefront of financial innovation. Your work will directly contribute to Tangram.ai’s mission of making GenAI accessible, scalable, and secure for enterprises. This role is ideal for those who thrive in dynamic, high-impact environments where technical precision meets real-world business outcomes.

What You Bring to the Table

We are seeking a seasoned professional with:

• 4–7+ Years of Experience: A proven track record in Software Engineering, DevOps, Platform Engineering, or a related field, with at least 2+ years specializing in MLOps or LLMOps.
• Deep Expertise in Kubernetes and OpenShift: Hands-on experience deploying, managing, and optimizing AI workloads in containerized environments, including Helm, Kustomize, and Kubernetes Operators.
• NVIDIA GPU Mastery: Extensive experience with NVIDIA GPUs, NVIDIA GPU Operator, and advanced GPU technologies like MIG and time-slicing to optimize AI performance.
• LLM and AI Platform Deployment: Direct experience deploying LLMs, NVIDIA NIM, Triton Inference Server, or similar enterprise AI platforms in production environments.
• Air-Gapped and Offline Deployment Knowledge: Familiarity with deploying AI solutions in disconnected or air-gapped environments, ensuring resilience and reliability.
• Security and Compliance Acumen: A strong understanding of enterprise authentication, authorization, and secrets management to align with banking and financial services regulations.
• Troubleshooting and Collaboration Skills: Exceptional problem-solving abilities and the capacity to work seamlessly with cross-functional teams, including clients, to drive successful deployments.

While not mandatory, the following will be highly valued:

• Experience deploying AI platforms specifically in Banking/BFSI or highly regulated industries.
• Certifications such as Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD).
• Familiarity with Graph Databases like Neo4j or ArangoDB.
• Experience with large-scale LLM inference and Retrieval-Augmented Generation (RAG) deployments.
• Proven expertise in GPU performance tuning and optimization.

Join Tangram.ai and be at the forefront of shaping the future of enterprise AI. Your expertise will not only drive innovation but also set new benchmarks for security, performance, and scalability in the banking sector.