Developer III - Software Engineering

Job Description

We are seeking a skilled and forward-thinking Cloud AI\/ML Engineer to lead the design, development, and support of scalable, secure, and high-performance generative AI applications on AWS . Youll operate at the crossroads of cloud engineering and artificial intelligence, enabling rapid and reliable delivery of cutting-edge AI solutions using services like Amazon Bedrock and SageMaker . This is an opportunity to join a collaborative team driving innovation in AI infrastructure, with a strong focus on automation, security, observability, and performance optimization. Roles and Responsibilities 1. AI\/ML Integration Utilize Amazon Bedrock for leveraging foundation models and Amazon SageMaker for training and deploying custom models. Design and maintain scalable generative AI applications using AWS-native AI\/ML tools and services. 2. Deployment Operations Build and manage CI\/CD pipelines to automate infrastructure provisioning and model lifecycle workflows. Monitor infrastructure and model performance using Amazon CloudWatch and other observability tools. Ensure production-grade availability, fault tolerance, and performance of deployed AI systems. 3. Security Compliance Enforce security best practices using IAM , data encryption, and access control policies. Maintain compliance with relevant organizational, legal, and industry-specific data protection standards. 4. Collaboration Support Partner with data scientists, ML engineers, and product teams to translate requirements into resilient cloud-native solutions. Diagnose and resolve issues related to model behavior, infrastructure health, and AWS service usage. 5. Optimization Documentation Continuously assess and optimize model performance , infrastructure cost , and resource utilization . Document deployment workflows, architectural decisions, and operational runbooks for team-wide reference. 6. Mentorship Guidance Mentor peers and junior engineers by sharing knowledge of AWS services and generative AI best practices . Must-Have Skills Experience Expertise in AWS services , particularly SageMaker, Bedrock, EC2, IAM , and related cloud-native tools. Strong coding skills in Python , with experience in developing AI applications. Hands-on experience with Docker for containerization and familiarity with Kubernetes for orchestration. Proven experience building and maintaining CI\/CD pipelines for AI\/ML workloads. Knowledge of data security , access control, and monitoring within cloud environments. Experience managing cloud-based data flows and infrastructure for ML workflows. Good-to-Have (Preferred) Skills AWS certifications, such as: AWS Certified Machine Learning Specialty AWS Certified DevOps Engineer Understanding of responsible AI practices , particularly in generative model deployment. Experience in cost optimization , auto-scaling , and resource management for production AI workloads. Familiarity with tools like Terraform, CloudFormation , or Pulumi for infrastructure as code (IaC). Exposure to multi-cloud or hybrid cloud strategies involving AI\/ML services. ","