Drive platform reliability, resiliency, operational excellence, disaster recovery, and production readiness
Leverage AI-assisted engineering tools such as GitHub Copilot, Amazon Q, OpenAI, Claude, Cursor, or similar technologies to improve developer productivity, automation, troubleshooting, and operational efficiency
Collaborate with development, architecture, security, and infrastructure teams to improve platform scalability, security posture, developer experience, and engineering productivity
Lead cloud modernization, automation, platform engineering, and DevSecOps initiatives while mentoring engineering teams on best practices
Qualifications
Required
Bachelor's or Master's degree
5–10 years of experience in DevOps, DevSecOps, Platform Engineering, Cloud Engineering, or related disciplines supporting enterprise-scale applications and distributed systems
3+ years in a senior technical role such as DevSecOps Lead, Platform Engineer, Senior DevOps Engineer, or Site Reliability Engineer (SRE)
Strong hands-on experience with AWS cloud services including EKS/ECS, Lambda, IAM, VPC, CloudWatch, S3, RDS, Kinesis, MQ, RedShift, Secrets Manager, SNS, SQS, EventBridge, and ElastiCache
Strong knowledge of cloud security including IAM, RBAC, encryption, OAuth2/OIDC, JWT, network security, and Zero Trust principles
Programming experience in Python, Bash, Go, or similar scripting languages
Familiarity with enterprise AI/LLM concepts including Prompt Engineering, RAG, Vector Databases, AI Agents, LLMOps, AI Security Guardrails, and Responsible AI practices
Preferred
Experience integrating and operating AI/LLM services using AWS Bedrock, Amazon Q, OpenAI, Azure AI, Anthropic Claude, or equivalent enterprise AI platforms
Experience supporting LLMOps pipelines, AI model deployment, governance, monitoring, and security
AWS, Kubernetes, Terraform, Security, DevOps, AI/ML, or related professional certifications