Senior AWS DevOps Engineer

About the Role

We are seeking a highly experienced Senior AWS DevOps Engineer to lead the design, automation, and scaling of our cloud infrastructure. This role is ideal for a DevOps professional with a strong background in AWS, serverless computing, and infrastructure automation—and a keen interest or experience in supporting machine learning and generative AI workloads in production.

Key Responsibilities

• Architect and maintain robust, scalable AWS infrastructure for production, development, and testing environments.

• Automate infrastructure using Terraform, CloudFormation, and CDK.

• Build and manage CI/CD pipelines for deploying microservices, serverless applications, and ML models.

• Design and manage serverless architectures using AWS Lambda, API Gateway, Step Functions, EventBridge, and DynamoDB.

• Support and optimize ML workflows and pipelines using tools such as SageMaker, ECS, or EKS.

• Collaborate with data scientists and ML engineers to productionize and monitor generative AI models and pipelines.

• Implement observability tools for performance monitoring, logging, and alerting (e.g., CloudWatch, Prometheus, Grafana, Datadog).

• Manage secure IAM policies, VPC configurations, and secrets across environments.

• Drive cost optimization and infrastructure efficiency across AWS services.

• Mentor junior engineers and contribute to DevOps best practices across the organization.

Required Skills and Experience

• 5+ years of experience in DevOps, SRE, or Cloud Infrastructure roles.

• Deep expertise with AWS (Lambda, ECS/EKS, S3, IAM, CloudWatch, CloudFront, etc.).

• Proven experience designing and operating serverless AWS infrastructure.

• Strong proficiency in Infrastructure as Code (Terraform, CloudFormation, or CDK).

• Experience with CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI, etc.).

• Hands-on experience supporting machine learning or AI workloads in production.

• Familiarity with SageMaker, Amazon Bedrock, or deploying custom generative AI models.

• Strong scripting skills (e.g., Python, Bash).

• Knowledge of container orchestration (Kubernetes, EKS) and Docker.

Preferred Qualifications

• AWS Certified DevOps Engineer or AWS Certified Machine Learning Specialty.

• Experience with generative AI frameworks (e.g., Hugging Face Transformers, LangChain, OpenAI APIs).

• Understanding of MLOps tools (MLflow, Weights & Biases, etc.).

• Familiarity with event-driven architectures and asynchronous systems.

• Experience in regulated environments (e.g., HIPAA, SOC 2, GDPR).

What We Offer

• Competitive salary and equity options

• Flexible remote-first working environment

• Access to cutting-edge AI/ML projects

• Professional development and certification budget

• Health insurance and wellness perks

• The opportunity to shape and scale modern cloud infrastructure at a tech-forward company