Cloud Platform Engineer - AI, Officer

Job Title:  DevOps Engineer – AI/ML Platform Experience:  8–12+ years   About the Role We are seeking a skilled DevOps Engineer with experience in AI/ML infrastructure to design, build, and maintain scalable, secure, and reliable cloud platforms that support AI and machine learning workloads. The ideal candidate will have strong expertise in cloud-native technologies, CI/CD, infrastructure automation, Kubernetes, and MLOps practices.

Design, implement, and manage cloud infrastructure for AI/ML applications and services. Build and maintain CI/CD pipelines for application and machine learning model deployments. Automate infrastructure provisioning using Infrastructure as Code (IaC) tools. Deploy and manage containerized workloads using Kubernetes. Implement MLOps workflows for model training, validation, deployment, and monitoring. Optimize cloud resources for performance, scalability, and cost efficiency. Monitor platform health, troubleshoot production issues, and ensure high availability. Implement security best practices, including secrets management, IAM, and compliance controls. Collaborate with data scientists, ML engineers, software developers, and platform teams. Establish observability solutions using logging, monitoring, and tracing tools.

DevOps & Cloud Strong experience with at least one major cloud platform: Amazon Web Services (AWS) Microsoft (Azure) Google (GCP) Expertise in Linux system administration. Experience with containerization technologies such as: Docker Kubernetes Strong knowledge of Infrastructure as Code: Terraform Ansible CI/CD tools such as: Jenkins GitHub Actions GitLab CI/CD AI / MLOps Experience supporting AI/ML workloads in production. Knowledge of MLOps frameworks and tools: MLflow Kubeflow Experience with model deployment, model serving, and monitoring. Understanding of GPU-based infrastructure and distributed training environments. Familiarity with vector databases, LLM applications, and generative AI workflows. Experience integrating AI services and APIs. Monitoring & Security Monitoring and observability: Prometheus Grafana OpenTelemetry Security and secrets management: HashiCorp Vault Knowledge of DevSecOps practices.

Experience with Large Language Models (LLMs) and Generative AI platforms. Experience with Retrieval-Augmented Generation (RAG) architectures. Certifications in AWS, Azure, GCP, Kubernetes, or Terraform. Experience managing multi-cloud or hybrid-cloud environments. Nice-to-Have: Python scripting and automation. Experience with data pipelines and streaming technologies. Knowledge of cost optimization for AI infrastructure. Experience building internal developer platforms and self-service infrastructure. Success Criteria Highly available and secure AI/ML platform. Automated deployment pipelines for applications and models. Reduced infrastructure provisioning time through automation. Improved reliability, observability, and operational efficiency of AI workloads.  Why this job is important to us The team you will be joining is a part of Charles River Development (or CRD), that became a part of State Street in 2018. CRD helps create enterprise investment management software solutions for large institutions in the areas of institutional investment, wealth management, and hedge funds. Together we have created the first open front-to-back platform - State Street Alpha, that was launched in 2019. Why this job is important to us The team you will be joining is a part of Charles River Development (or CRD), that became a part of State Street in 2018. CRD helps create enterprise investment management software solutions for large institutions in the areas of institutional investment, wealth management and hedge funds. Together we have created the first open front-to-back platform - State Street Alpha, that was launched in 2019.

Strong experience in enterprise application architecture and