Senior Software Engineer - Infrastructure - AI/ML

Mitratech is a team of innovators building world-class products for Legal, Risk, Compliance, and HR functions. We are seeking a Senior Infrastructure Engineer to design, build, and maintain scalable cloud infrastructure supporting AI and ML workloads. The role involves deep expertise in AWS, containerization, CI/CD, and automation.

• Design, deploy, and maintain scalable and secure infrastructure supporting AI and ML workloads
• Build and maintain AWS cloud environments for compute (EC2, ECS/EKS, Lambda), storage (S3, EFS, FSx), and networking (VPC, Transit Gateway, PrivateLink, Route 53, load balancers)
• Implement security best practices using IAM, KMS, Secrets Manager, GuardDuty, and Security Hub
• Support and optimize AI/ML workloads across AWS services (SageMaker, Bedrock, Batch, Step Functions)
• Develop and maintain Infrastructure as Code (IaC) using Terraform, AWS CDK, and CloudFormation
• Manage containerized workloads and orchestration platforms (Docker, EKS, Fargate), including GPU scheduling and scaling
• Set up and maintain monitoring and observability frameworks using CloudWatch and OpenTelemetry
• Build and manage CI/CD pipelines (CircleCI, GitHub Actions, GitLab CI) for infrastructure automation and ML/Gen AI deployments
• Collaborate with ML and Generative AI teams to scale models, optimize performance, and design efficient prompt or inference pipelines
• Develop runbooks and SOPs for AI service deployment, troubleshooting, and performance optimization
• Ensure security, compliance, and data protection across AI datasets and environments

• Deep expertise in AWS cloud services across compute, storage, networking, and security domains
• Proficiency in container orchestration (Kubernetes/EKS) and infrastructure automation tools
• Hands-on experience with IaC tools such as Terraform, AWS CDK, or CloudFormation
• Familiarity with monitoring, logging, and observability stacks (Prometheus, Grafana, OpenTelemetry)
• Experience implementing CI/CD pipelines for automated deployment and testing
• Understanding of AI/ML concepts including model deployment, inference scaling, and LLM performance tuning
• Working knowledge of security best practices, IAM roles, encryption, and compliance controls
• Excellent collaboration and communication skills to partner with ML engineers, data scientists, and product teams
• A Master’s degree in Machine Learning, Computer Science with preference for NLP specialization