AI Engineer (Platform Engineering)

About the Role

Cake, a leading Vietnamese digital bank with a rapidly growing user base exceeding 6 million, is on a mission to become the NextGen AI Bank. We leverage cutting-edge AI and data science across all our products and services — and we believe generative AI will redefine what banking can be: smarter, faster, and more human.

We are seeking an AI Engineer who bridges the gap between pure AI/ML and high-performance software engineering. This is a hybrid role combining AI/ML Ops platform management, rigorous inference optimization, and AI backend engineering. You will be responsible for taking trained models out of the lab and orchestrating them into resilient, ultra-low-latency production systems.

This is an opportunity to own the deployment lifecycle and infrastructure architecture—building complex agentic workflows and self-hosted clusters that power critical financial operations.

Key Responsibilities

• Inference & Optimization: Deploy, profile, and optimize models for latency, throughput, and cost.
• MLOps & Platform: Build and maintain CI/CD and automated testing pipelines for ML models, and help operate self-hosted GPU clusters on Kubernetes.
• AI Software & Agents: Implement AI agent workflows, APIs, memory layers, and backend services that connect inference engines to client-facing applications.
• Developer Productivity: Use AI coding assistants and modern dev tools to prototype, debug, and ship faster.
• Security & Compliance: Follow security practices so infrastructure, data pipelines, and open-source integrations comply with regional data sovereignty regulations.
• Collaboration: Work with ML researchers, product, backend and SRE teams to take POCs into production.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.
• Engineering experience in MLOps, ML infrastructure, or backend/systems engineering — around 1–3 years for Middle; for Junior, strong internships or projects count.
• Solid programming skills in Python; C++ or Go is a plus.
• Hands-on experience with Docker and working knowledge of Kubernetes, ideally deploying on GCP.
• Experience building APIs (FastAPI/gRPC) and a working understanding of system design, including how to handle non-deterministic AI outputs.
• Understanding of ML/DL fundamentals and model inference — e.g., batching, quantization, and serving frameworks such as vLLM, Triton, or TensorRT.
• A product-oriented mindset and eagerness to debug performance issues across the stack.

Nice-to-Have

• Hands-on experience building and orchestrating AI agents, including identity layers and RAG pipelines.
• Experience extracting data from complex documents or working with specialized open-source models.
• Infrastructure-as-code (e.g., Terraform) and experience with self-hosted or bare-metal GPU environments.
• Previous experience deploying AI or secure software in the fintech, banking sectors.
• Active contributions to open-source projects.

Why You’ll Love Working at Cake

• Build generative AI systems used daily by 6+ million users — your work makes an immediate, tangible impact.
• End-to-end ownership: from foundation-model research to production deployment.
• Work with a cutting-edge cloud-native stack (GCP, Vertex AI, Kubernetes, Airflow) and large-scale GPU compute.
• Collaborative, high-performing tech culture where experimentation and innovation are encouraged.
• Competitive compensation and the opportunity to grow within a fast-scaling digital bank.

Our Benefits

• Competitive compensation including a 13th-month wage and up to 3 months of performance-based bonus.
• MacBooks are supplied to all technical team members.
• BE Corp budget (varies by level) for transportation, food, and car bookings in the Be application.
• Social insurance contribution amount based on individual level.
• Annual health checks and premium medical healthcare (PTI) after probation.
• 15 days of annual leave for all staff.
• Company trips, team-building activities, and happy-hour events on a quarterly or annual basis.