About the job
The AI Agentic Team will be responsible for designing, building, and operating intelligent agents end to end. They develop agent logic, workflows, integrations, and decision frameworks, then deploy those agents into production and own their ongoing behavior, reliability, and impact. The team monitors agent performance validates AI driven actions with human judgment, and iterates on designs as systems encounter real world complexity. By owning both construction and operations, they ensure agentic platforms are not just innovative, but reliable, secure, and scalable in production.
Responsibilities
Design, implement, and operate cloud infrastructure supporting scalable, highly available AI-enabled and Agentic platforms.
Apply Infrastructure as Code (IaC) practices (e.g., Terraform, Packer, Ansible) to provision and manage cloud resources consistently and securely.
Monitor platform health using metrics, logs, dashboards, and alerts, applying critical thinking to distinguish infrastructure, application, and AI-driven failures.
Lead troubleshooting and resolution of complex cloud and platform issues, including distributed system and integration failures.
Develop and maintain automation and tooling (primarily Python and shell scripting) to improve reliability, diagnostics, and operational efficiency.
Implement and evolve observability solutions (e.g., Prometheus, Splunk, Grafana, CloudWatch) to improve system transparency and alert quality.
Collaborate with application, data, and AI teams to ensure platforms are operable, observable, and scalable prior to and after release.
Support CI/CD pipelines and release workflows, enabling safe and repeatable deployments across environments.
Ensure secure cloud operations, including secrets management, access controls, encryption, and secure networking practices.
Apply foundational AI literacy to understand agent lifecycles, orchestration patterns, and non-deterministic execution behaviors that impact operations.
Use AI-assisted tools to enhance investigation, documentation, and optimization, while validating outputs with sound engineering judgment.
Contribute to and maintain runbooks, platform documentation, and operational standards.
Participate in on-call rotations and act as an escalation point during production incidents.
Perform other duties and responsibilities as assigned.
Qualifications
Minimum
Cloud Infrastructure Engineering (AWS, Azure, or GCP)
Infrastructure as Code (Terraform, Packer, Ansible, or equivalent)
Python Programming for automation and operational tooling
Monitoring, Logging, and Alerting Systems
CI/CD Tools and Release Automation
Security Fundamentals (IAM, secrets management, encryption, network security)
Preferred
Experience supporting AI, ML, or Agentic platforms in production
Familiarity with data and streaming platforms (e.g., S3, SQS, Kafka-like systems)
Understanding of networking and protocol standards
Exposure to hardware security modules (HSMs) or advanced key management solutions
Experience operating large-scale distributed systems
Cloud cost optimization and performance tuning experience